Veranstaltungsverzeichnis

Lehrveranstaltungen SoSe 2024

Fachbereich 03: Mathematik/Informatik

Veranstaltungen anzeigen: alle | in englischer Sprache | für ältere Erwachsene | mit Nachhaltigkeitszielen

Digitale Medien, B.Sc.

3. Studienjahr

B-MI-9

Auch Module aus B-MI-8 hier wählbar.
Hinweis: Studierende, die das Software-Projekt machen möchten, müssen bitte alle drei angebotenen Veranstaltungen hierzu belegen: 03-BA-901.01a (SWP1), 03-BA-901.01b (Datenbankgrundlagen) und 03-BA-901.01c (SWP Praktikum).
Bei Vorliegen der jeweiligen inhaltlichen Voraussetzungen auch: M-MI/ M-MI-d des Master
VAKTitel der VeranstaltungDozentIn
03-IBAP-ML (03-BB-710.10)Grundlagen des Maschinellen Lernens (in englischer Sprache)
Fundamentals of Machine Learning

Kurs
ECTS: 6

Termine:
wöchentlich Mo 14:00 - 16:00 MZH 1470 Übung
wöchentlich Mi 08:00 - 10:00 MZH 1380/1400 Vorlesung
wöchentlich Mi 10:00 - 12:00 MZH 1380/1400 GW2 B1820 Übung

Einzeltermine:
Mi 12.06.24 08:00 - 09:30 MZH 1380/1400
Di 23.07.24 14:00 - 16:00 NW1 H 1 - H0020

Schwerpunkt: AI
https://lvb.informatik.uni-bremen.de/ibap/03-ibap-ml.pdf
Die Übungen starten in der 2. Semesterwoche.

Tanja Schultz
Felix Putze
Darius Ivucic
Gabriel Ivucic
Zhao Ren

B-MA-2

Auch Module aus den Bereichen B-MI-8 und B-MI-9 sind hier wählbar.
Für Lehrveranstaltungen dieses Moduls der Hochschule für Künste bitte das dortige Lehrveranstaltungsverzeichnis ansehen: http://www.hfk-bremen.de/t/digitale-medien
VAKTitel der VeranstaltungDozentIn
03-IBVA-DSV (03-BE-802.98a)Data Science and Visualization (in englischer Sprache)

Kurs
ECTS: 6

Termine:
wöchentlich Mo 10:00 - 12:00 MZH 5600 Kurs
wöchentlich Mo 12:00 - 14:00 MZH 5600 Kurs

Eine Doppelanerkennung von 'Data Science' und 'Data Science and Visualization' ist nicht möglich.
https://lvb.informatik.uni-bremen.de/ibv/03-ibva-dsv.pdf

The class will provide an introduction to data science and information visualization. For this, the programming language Python will be used (and taught). For creating data visualizations, you will be able to choose among a series of tools (e.g., Plotly, Observable, etc.)

We will explore different concepts from the fields of human-computer interaction, data visualization, and computer-supported collaborative work. You will learn about:
      • Basic statistics
      • Visualization techniques
      • Interaction design
Exploratory data analysis and evaluation, as an integral part of data science, will also be taught. The course will involve applying the learned techniques to real-world datasets to develop a custom project.

This class is taught in person and in English. Use material like the coursebook to learn more about the topics as we progress in the course.

Dr. Gabriela Molina Leon
IBVP-AKRActionable Knowledge Representation (in englischer Sprache)

Vorlesung
ECTS: 6

Termine:
wöchentlich Di 10:00 - 12:00 Vorlesung
wöchentlich Di 12:00 - 14:00 Übung

Die Veranstaltung findet im TAB in Raum 0.30 statt.
https://lvb.informatik.uni-bremen.de/ibv/03-ibvp-akr.pdf

This course deals with the idea of bringing knowledge into applications to support users in daily life. It therefore covers topics on how knowledge can be represented to be machine-understandable, how knowledge can be acquired from different sources (including Web scraping) and how such different knowledge chunks can be linked. It will further discuss how to reason about knowledge and how different agents like websites, AR applications or robots can use knowledge to support users in their daily life. All exercises will be available in platform-independent jupyter notebooks based on python and have low software requirements.

Robert Porzel
Michaela Kümpel

Graduiertenseminare

VAKTitel der VeranstaltungDozentIn
03-IGRAD-CoSy (03-05-H-711.91)Graduiertenseminar Cognitive Systems (in englischer Sprache)

Seminar

Termine:
zweiwöchentlich (Startwoche: 16) Mi 14:00 - 17:00 Graduiertenseminar
Thomas Dieter Barkowsky

Informatica Feminale

VAKTitel der VeranstaltungDozentIn
META-2024-ALL-IF27. internationale Informatica Feminale (in englischer Sprache)
Informatica Feminale - Summer University for Women in Computing
Sommeruniversität für Frauen in der Informatik /Summer University for Women in Computing

Blockveranstaltung
ECTS: 1-3 (je Kurs/for every course)

60 Lehrveranstaltungen in Deutsch und Englisch für Bachelor- und Masterstudentinnen aller Fächer. Als General Studies sowie teilweise als Fachstudium im Sommersemester 2024 sowie im Wintersemester 2024/25 anerkannt. Alle Einzelangaben, Zeiten und Anmeldungen jederzeit nur über die Website https://www.informatica-feminale.de.
60 courses in German and English for women Bachelor and Master students from all fields of study. Courses are part of General Studies, some are accepted in Informatics; in the summer semester 2024 as well as in winter semester 2024/25. Further information, schedules and registration only on the website https://www.informatica-feminale.de.

Veronika Oechtering
Henrike Illig

Digitale Medien, M.Sc.

1st academic year

Veranstaltungen von MG ( Media Design) und MT ( Media Theory) finden primär in der HfK statt.
Das Seminar Introduction to Digital Media wird von der HfK angeboten.

M-MI (Media Informatics)

VAKTitel der VeranstaltungDozentIn
03-IMAA-CTHCICurrent Topics in Human Computer Interaction (in englischer Sprache)

Kurs
ECTS: 6

Termine:
wöchentlich Mi 10:00 - 14:00 SFG 0150 Kurs

Profil: DMI
Schwerpunkt: IMA-DMI, IMA-VMC
https://lvb.informatik.uni-bremen.de/imaa/03-imaa-cthci.pdf

Prof. Dr. Tanja Döring
03-IMAA-EC (03-MB-804.03)Entertainment Computing (in englischer Sprache)

Vorlesung
ECTS: 6

Termine:
wöchentlich Di 10:00 - 12:00 MZH 6200 Vorlesung
wöchentlich Di 12:00 - 14:00 MZH 6200 Übung

Profil: DMI
Schwerpunkt: IMK-DMI, IMA-VMC
https://lvb.informatik.uni-bremen.de/imaa/03-imaa-ec.pdf

Prof. Dr. Rainer Malaka
Rachel Ringe
Leon Tristan Dratzidis
Nima Zargham
03-IMAA-MAD (03-ME-804.06)Mobile App Development (in englischer Sprache)

Vorlesung
ECTS: 6

Termine:
wöchentlich Mo 12:00 - 14:00 MZH 6200 Vorlesung
wöchentlich Mo 14:00 - 16:00 MZH 6200 Übung

Profil: DMI
Schwerpunkt: IMA-DMI, IMVA-DMI
https://lvb.informatik.uni-bremen.de/imva/03-imva-mad.pdf
Die Veranstaltung richtet sich an Studenten der Informatik und Digitalen Medien. In Gruppenarbeit sollen die Studierenden semesterbegleitend ein App-Projekt umsetzen. In der Vorlesung werden alle relevanten Informationen der modernen Softwareentwicklung, mit Fokus auf die mobile App-Entwickung, vermittelt. Dazu gehören Themen wie mobiles Testing, Scrum, UX Design, Evaluation & Nutzertests, Design Patterns und Cross-Plattform-Entwicklung. Das Ziel dabei ist die Vermittlung von praxisrelevantem Wissen aus dem Alltag eines erfolgreichen Unternehmens.

Prof. Dr. Rainer Malaka
David Ruh
Nicolas Autzen
03-IMAP-DIS (03-MB-703.02)Design of Information Systems (in englischer Sprache)

Vorlesung
ECTS: 6

Termine:
wöchentlich Mo 12:00 - 14:00 MZH 1450 Vorlesung
wöchentlich Di 08:00 - 10:00 MZH 1110 Übung

Profil: SQ.
Schwerpunkt: IMVP-DMI, IMVP-SQ
https://lvb.informatik.uni-bremen.de/imap/03-imap-dis.pdf
Die Veranstaltung ist inhaltlich identisch mit "Entwurf von Informationssystemen" (keine Doppelanerkennung möglich).

Martin Gogolla
03-IMVA-EI (03-ME-899.03)Embodied Interaction (in englischer Sprache)

Kurs
ECTS: 6

Termine:
wöchentlich Do 08:00 - 10:00 MZH 1110 Kurs
wöchentlich Do 10:00 - 12:00 MZH 1110 Kurs

Profil: DMI.
Schwerpunkt: IMVA-DMI, IMVA-VMC
https://lvb.informatik.uni-bremen.de/imva/03-imva-ei.pdf

Robert Porzel
Prof. Dr. Rainer Malaka
03-IMVA-GACGenerative AI and Creativity - Understanding the Impact on Digital Media (in englischer Sprache)

Kurs
ECTS: 6

Termine:
wöchentlich Mo 12:00 - 14:00 MZH 1470 Kurs
wöchentlich Mi 12:00 - 14:00 MZH 1470 Seminar

4 SWS, Schwerpunkt: IMVA-DMI
https://lvb.informatik.uni-bremen.de/imva/03-imva-gac.pdf

In this seminar, we want to investigate current tools and models (e.g., Dall-E2, ChatGPT) for creating content. We will discuss the idea and design and the implications for artists, developers, and researchers. Therefore, we will read current research papers and develop applications that use these models. We want to design and create new interfaces and ideas to support users with these tools. The course is open to Digital Media and Computer Science students.

Dr. Nina Wenig
03-IMVP-ECLEdge Computing Lab (in englischer Sprache)

Kurs
ECTS: 6

Termine:
wöchentlich Mo 16:00 - 18:00 MZH 1110 Kurs


Peter Fereed Haddawy
Prof. Dr. Anna Förster
Thomas Dieter Barkowsky
03-IMVP-MPAR (03-ME-708.05)Massively-Parallel Algorithms (in englischer Sprache)

Vorlesung
ECTS: 6

Termine:
wöchentlich Di 16:00 - 18:00 MZH 1110 Vorlesung
wöchentlich Mi 08:00 - 10:00 MZH 1100 Übung

https://lvb.informatik.uni-bremen.de/imvp/03-imvp-mpar.pdf
Profil: SQ, KIKR, DMI.
Schwerpunkt: SQ, AI, DMI, VMC
Some prior expertise in C will be helpful. The lecture will be held in German or English, depending on demand.
https://cgvr.cs.uni-bremen.de/teaching/

Prof. Dr. Gabriel Zachmann

M-MI-d ( Media Informatics in deutscher Sprache )

VAKTitel der VeranstaltungDozentIn
03-IMS-APMSK (03-ME-711.09)Ausgewählte Probleme der multisensorischen Kognition (in englischer Sprache)
Selected Problems of Multisensory Cognition

Seminar
ECTS: 3

Termine:
wöchentlich Do 12:00 - 14:00 CART Rotunde - 0.67 Seminar

Profil: KIKR, DMI.
https://lvb.informatik.uni-bremen.de/ims/03-ims-apmsk.pdf
Die Veranstaltung findet in Englischer Sprache statt.

Christop W. Zetzsche-Schill
Kerstin Schill

M-MT (Media Theory)

Additional courses can be found at the HfK website (http://www.hfk-bremen.de/t/digitale-medien).
VAKTitel der VeranstaltungDozentIn
03-IMVA-TMPThe Machinic Project (in englischer Sprache)

Seminar
ECTS: 6

Termine:
wöchentlich Mo 10:00 - 12:00 MZH 1450 Seminar
wöchentlich Di 10:00 - 12:00 MZH 1450 Seminar


Dr. Bernhard Robben
Frieder Nake
09-71-A.2-1Course 1: Mediatization (in englischer Sprache)

Seminar

Termine:
wöchentlich Mo 14:00 - 16:00 IW3 0330 (2 SWS)


Prof. Dr. Peter Gentzel

M-MA-2 (Special Topics in Digital Media)

All M-MI, M-MD, M-MT courses can be taken as M-MA-2
VAKTitel der VeranstaltungDozentIn
03-DMM-MA-2-ONTHON THINKING. Logic – algorithmic – dialectic (in englischer Sprache)

Seminar
ECTS: 3

Termine:
wöchentlich Di 14:00 - 16:00 MZH 1450 Seminar
Frieder Nake
03-IMS-MBCDLMultimodal Biosignal Collection in Daily Life (in englischer Sprache)

Seminar
ECTS: 3

Einzeltermine:
Mi 03.04.24 10:00 - 12:00 Auftakttermin
Mi 10.04.24 10:00 - 12:00 CART 0.01
Mi 08.05.24 10:00 - 12:00 CART 0.01
Mi 29.05.24 10:00 - 12:00 CART 0.01
Mi 26.06.24 10:00 - 12:00 CART 0.01

Auftakttermin am 03.04.2024 von 10-12h in Raum 0.01.
Weitere Termine werden dann abgesprochen.

Jana Schill
03-IMVA-ACSSApplied Computer Science in Sports (in englischer Sprache)

Kurs
ECTS: 6

Termine:
wöchentlich Mi 14:00 - 18:00 MZH 1110 Kurs

Schwerpunkt: IMVA-AI, IMVA-DMI
https://lvb.informatik.uni-bremen.de/imva/03-imva-acss.pdf
The aim of this course is to create an understanding of the major aspects of sports applications. The course is split into two parts: the first half has a classic lecture/tutorial style, whereas the second half will focus on the creation of individual sports applications.

The lectures will explain the necessary fundamentals, such as sensor technology, user feedback, and the conduction of empirical studies, along with a number of inspiring examples.

In the project part, own prototypes for sports applications are developed in small groups. The exact application as well as the technical implementation approach can be chosen freely. The final graded outcome of the course will be a small sports application about which a presentation has to be held and a documentation in a scientific paper style has to be written.

The course will be held in English.

Schwerpunkt: AI, DMI

Robert Porzel
Dr. Tim Laue
Bastian Dänekas
03-IMVA-DSSDecision Support Systems (in englischer Sprache)

Vorlesung
ECTS: 6

Termine:
wöchentlich Mi 08:15 - 10:00 MZH 1110
wöchentlich Mi 10:00 - 12:00 MZH 1110 Vorlesung und Übung


Dr. Gerhard Klassen
Dr. Marc Wyszynski
Prof. Dr. Dr. Björn Niehaves
Sebastian Weber
Patricia Zauchner

M-MA-31 (Project Preparation)

VAKTitel der VeranstaltungDozentIn
03-IBVA-DSV (03-BE-802.98a)Data Science and Visualization (in englischer Sprache)

Kurs
ECTS: 6

Termine:
wöchentlich Mo 10:00 - 12:00 MZH 5600 Kurs
wöchentlich Mo 12:00 - 14:00 MZH 5600 Kurs

Eine Doppelanerkennung von 'Data Science' und 'Data Science and Visualization' ist nicht möglich.
https://lvb.informatik.uni-bremen.de/ibv/03-ibva-dsv.pdf

The class will provide an introduction to data science and information visualization. For this, the programming language Python will be used (and taught). For creating data visualizations, you will be able to choose among a series of tools (e.g., Plotly, Observable, etc.)

We will explore different concepts from the fields of human-computer interaction, data visualization, and computer-supported collaborative work. You will learn about:
      • Basic statistics
      • Visualization techniques
      • Interaction design
Exploratory data analysis and evaluation, as an integral part of data science, will also be taught. The course will involve applying the learned techniques to real-world datasets to develop a custom project.

This class is taught in person and in English. Use material like the coursebook to learn more about the topics as we progress in the course.

Dr. Gabriela Molina Leon

2nd academic year

Graduate Seminars

VAKTitel der VeranstaltungDozentIn
03-IGRAD-CoSy (03-05-H-711.91)Graduiertenseminar Cognitive Systems (in englischer Sprache)

Seminar

Termine:
zweiwöchentlich (Startwoche: 16) Mi 14:00 - 17:00 Graduiertenseminar
Thomas Dieter Barkowsky

General Studies

Concerning the language, usually you can see by the title whether a course is in English or German.
VAKTitel der VeranstaltungDozentIn
META-2024-ALL-IF27. internationale Informatica Feminale (in englischer Sprache)
Informatica Feminale - Summer University for Women in Computing
Sommeruniversität für Frauen in der Informatik /Summer University for Women in Computing

Blockveranstaltung
ECTS: 1-3 (je Kurs/for every course)

60 Lehrveranstaltungen in Deutsch und Englisch für Bachelor- und Masterstudentinnen aller Fächer. Als General Studies sowie teilweise als Fachstudium im Sommersemester 2024 sowie im Wintersemester 2024/25 anerkannt. Alle Einzelangaben, Zeiten und Anmeldungen jederzeit nur über die Website https://www.informatica-feminale.de.
60 courses in German and English for women Bachelor and Master students from all fields of study. Courses are part of General Studies, some are accepted in Informatics; in the summer semester 2024 as well as in winter semester 2024/25. Further information, schedules and registration only on the website https://www.informatica-feminale.de.

Veronika Oechtering
Henrike Illig

Industrial Mathematics & Data Analysis, M.Sc.

Foundations (33 CP)

Module: Modeling Project (15 CP)

Compulsory module in which you must attend the following lecture this semester:
VAKTitel der VeranstaltungDozentIn
03-M-MP-1Modeling Project (Part 1) (in englischer Sprache)

Seminar
ECTS: 6

Termine:
wöchentlich Di 10:00 - 12:00 MZH 2340 Seminar

Over the course of two semesters, the participants of the modeling project work in teams on a project in which they are supposed to use the mathematical knowledge they have already acquired in applications outside of mathematics. The project partners can be industrial companies or research institutes.

Tobias Kluth
Peter Maaß

Area of Focus: Data Analysis (45 CP)

Area of Focus (27 CP)

The modules Special Topics Data Analysis A and Special Topics Data Analysis B (9 CP each) are mandatory. In addition, EITHER the module Special Topics Data Analysis C OR the module Advanced Communications Data Analysis (9 CP each) must be studied.

Module: Advanced Communications Data Analysis (2 x 4,5 CP = 9 CP)

Compulsory module in which you must attend a total of two seminars with 4,5 CP each. This semester you can choose from the following seminars:
VAKTitel der VeranstaltungDozentIn
03-M-AC-21Deep Learning for Inverse Problems (in englischer Sprache)

Seminar
ECTS: 4,5/6

Termine:
wöchentlich Mo 14:00 - 16:00 MZH 2340 Seminar
Peter Maaß
03-M-AC-22Advanced Communication Analysis (in englischer Sprache)

Seminar
ECTS: 4,5/6

Termine:
wöchentlich Mi 12:00 - 14:00 MZH 4140 Seminar

Einzeltermine:
Fr 24.05.24 12:00 - 16:00 MZH 1380/1400

In the Seminar Analysis advanced topics in the area of analysis are discussed. The precise topic for Summer semester 2024 will be decided upon with the participants

Prof. Dr. Anke Dorothea Pohl
03-M-AC-23Advanced Robust Control (in englischer Sprache)

Seminar
ECTS: 4,5 / 6

Termine:
wöchentlich Do 10:00 - 12:00 MZH 2340 Seminar
Dr. Chathura Wanigasekara
03-M-AC-28Advanced Numerical Methods for Partial Differential Equations (in englischer Sprache)

Seminar
ECTS: 4,5 / 6

Termine:
wöchentlich Mo 16:00 - 18:00 MZH 2340 Seminar

Seminar on advanced numerical methods for partial differential equations

Alfred Schmidt

Modules: Special Topics Data Analysis (A, B, and C with 9 CP each)

Compulsory modules in which you must attend one lecture each. This semester you can choose from the following lectures:
VAKTitel der VeranstaltungDozentIn
03-M-SP-12High-Performance-Visualisierung (in englischer Sprache)
High-Performance Visualization
Interaktive Exploration zur Analyse von extrem großen wissenschaftlichen Daten

Vorlesung
ECTS: 4,5 / 6

Termine:
wöchentlich Do 14:00 - 16:00 MZH 1110 Lecture and Exercise

Einzeltermine:
Do 11.07.24 14:00 - 18:00 MZH 1110
Do 22.08.24 - Fr 23.08.24 (Do, Fr) 08:00 - 14:00 MZH 5500

The lecture addresses Interactive Visualization of Huge Scientific Datasets. More information can also be found on the Homepage: https://www.uni-bremen.de/ag-high-performance-visualization

Die Vorlesung beschäftigt sich mit den mathematischen Grundlagen der wissenschaftlichen Visualisierung und behandelt Methoden für das parallele Post-Processing großer wissenschaftlicher Datensätze. Anwendungsbeispiele werden anhand der Open-Source-Software ParaView erläutert.
Homepage zur Veranstaltung: https://www.uni-bremen.de/ag-high-performance-visualization

Prof. Dr. Andreas Gerndt
03-M-SP-15Analytic and Discrete Convex Geometry (in englischer Sprache)

Vorlesung
ECTS: 9

Termine:
wöchentlich Mo 12:00 - 14:00 MZH 4140 Lecture
wöchentlich Mi 10:00 - 12:00 MZH 1100 MZH 5220 (Didaktik-Labor) Lecture
wöchentlich Mi 12:00 - 14:00 MZH 3150 Exercise

Convex Geometry plays an essential role in several branches of Mathematics, from Discrete Mathematics to Harmonic Analysis. We will discuss some major analytic and discrete aspects of convex geometry and some applications. Our topics will range from the boundary structure of convex bodies, particularly polytopes, to Hadwiger's volume characterisation, via geometric and functional inequalities, as well as geometric and analytic symmetrization techniques.

Eugenia Saorin Gomez
03-M-SP-16Mathematical Foundations of Machine Learning (in englischer Sprache)

Vorlesung
ECTS: 9

Termine:
wöchentlich Mo 12:00 - 14:00 MZH 2340 Lecture
wöchentlich Di 12:00 - 14:00 MZH 2340 Lecture
wöchentlich Di 14:00 - 16:00 MZH 2340 Exercise

This course deals with the mathematical foundations of machine learning with a strong focus on classical theory and well-established algorithms like, for example, support vector machines for classification, ridge regression, principal component analysis for dimensionality reduction and k-means clustering. In addition, deep learning with neural networks will be briefly discussed towards the end of the course.

Peter Maaß
Dr. Matthias Beckmann
03-M-SP-22Linear and Generalized Linear Regression (Statistics II) (in englischer Sprache)

Vorlesung
ECTS: 9

Termine:
wöchentlich Mi 08:00 - 10:00 MZH 7200 Lecture
wöchentlich Mi 10:00 - 12:00 MZH 7200 Exercise
wöchentlich Do 08:00 - 10:00 MZH 7200 Lecture

Einzeltermine:
Do 25.07.24 10:00 - 12:00 MZH 7200
Maryam Movahedifar
03-M-SP-33Semiparametric Models (in englischer Sprache)

Vorlesung
ECTS: 9

Termine:
wöchentlich Di 09:00 - 10:30 Vorlesung
wöchentlich Mi 14:00 - 16:00 Übung
wöchentlich Fr 12:30 - 14:00 Vorlesung

Die Veranstaltung findet im KKSB statt.

The course will provide an introduction into the theory of semiparametric models. We will introduce and discuss the mathematical statistical theory for such models and will illustrate the utility of semiparametric models with a number of concrete models and data examples. Hence, the lecture and exercises will cover theoretical and practical aspects of semiparametric models. We will use the open statistical software R for the data applications.

Prof. Dr. Werner Brannath
03-M-SP-34Differential Geometry (in englischer Sprache)

Vorlesung
ECTS: 9

Termine:
wöchentlich Di 10:00 - 12:00 MZH 1110 MZH 4140 Lecture
wöchentlich Di 12:00 - 14:00 MZH 1470 Exercise
wöchentlich Mi 16:00 - 18:00 MZH 4140 Lecture

This course will cover manifolds, vector bundles, embeddings and submersions, integral curves and flows, basics of Lie groups, differential forms and integration, Riemannian metrics, geodesics, connections, curvature, and further topics.

Prof. Dr. Anke Dorothea Pohl
03-M-SP-35Selected Topics in Convex Optimization (in englischer Sprache)

Vorlesung
ECTS: 9

Termine:
wöchentlich Mo 10:00 - 12:00 MZH 2340 Lecture
wöchentlich Mi 10:00 - 12:00 MZH 2340 Lecture
wöchentlich Mi 12:00 - 14:00 MZH 2490 (Seminarraum) Exercise

The course will discuss convex optimisation problems and present and analyse algorithms that solve them. Topics will include proximal splitting, acceleration, stochastic algorithms, and performance estimation.

Sebastian Banert
Dirk Lorenz
03-M-SP-36Selected Topics on Optimization for Machine Learning (in englischer Sprache)

Vorlesung
ECTS: 9

Termine:
wöchentlich Do 14:00 - 16:00 MZH 2340 Lecture
wöchentlich Fr 10:00 - 12:00 MZH 2340 Lecture
wöchentlich Fr 12:00 - 14:00 MZH 2340 Exercise
Dirk Lorenz
Lionel Ngoupeyou Tondji

Extension (18 CP)

Module: Advanced Communications Industrial Mathematics (2 x 4,5 CP = 9 CP)

Compulsory module in which you must attend a total of two seminars with 4,5 CP each. This semester you can choose from the following seminars:
VAKTitel der VeranstaltungDozentIn
03-M-AC-21Deep Learning for Inverse Problems (in englischer Sprache)

Seminar
ECTS: 4,5/6

Termine:
wöchentlich Mo 14:00 - 16:00 MZH 2340 Seminar
Peter Maaß
03-M-AC-22Advanced Communication Analysis (in englischer Sprache)

Seminar
ECTS: 4,5/6

Termine:
wöchentlich Mi 12:00 - 14:00 MZH 4140 Seminar

Einzeltermine:
Fr 24.05.24 12:00 - 16:00 MZH 1380/1400

In the Seminar Analysis advanced topics in the area of analysis are discussed. The precise topic for Summer semester 2024 will be decided upon with the participants

Prof. Dr. Anke Dorothea Pohl
03-M-AC-23Advanced Robust Control (in englischer Sprache)

Seminar
ECTS: 4,5 / 6

Termine:
wöchentlich Do 10:00 - 12:00 MZH 2340 Seminar
Dr. Chathura Wanigasekara
03-M-AC-28Advanced Numerical Methods for Partial Differential Equations (in englischer Sprache)

Seminar
ECTS: 4,5 / 6

Termine:
wöchentlich Mo 16:00 - 18:00 MZH 2340 Seminar

Seminar on advanced numerical methods for partial differential equations

Alfred Schmidt

Module: Special Topics Industrial Mathematics A (9 CP)

Compulsory module in which you must attend one lecture. This semester you can choose from the following lectures:
VAKTitel der VeranstaltungDozentIn
03-IMAT-APX (03-ME-602.99a)Approximation Algorithms (in englischer Sprache)

Kurs
ECTS: 6

Termine:
wöchentlich Di 10:00 - 12:00 MZH 3150 Kurs
wöchentlich Do 14:00 - 16:00 MZH 1470 MZH 5500 Übung

Profil: SQ, KIKR.
Schwerpunkt: IMA-SQ, IMVT-AI, IMVT-VMC
weitere Studiengänge: M-M-Alg-Num, M-T
https://lvb.informatik.uni-bremen.de/imat/03-imat-apx.pdf

A large number of problems arising in practical scenarios like communication, transportation, planning, logistics etc. can be modeled as combinatorial optimization problems. In most cases, these problems are computationally intractable and one often resorts to heuristics that provide sufficiently good solutions in reasonable amount of runtime. However, in most cases, such heuristics do not provide a worst case guarantee on the performance in comparison to the optimum solution. In this course, we shall study algorithms for combinatorial optimization problems which can provide strong mathematical guarantees on performance. The course aims at developing a toolkit for solving such problems. The lectures will consist of designing polynomial-time algorithms and proving rigorous bounds on their worst case performances.
We review many classical results in the field of approximation algorithms, highlighting different techniques commonly used for the design of such algorithms. Among others, we will treat the following topics:
• Greedy algorithms and Local Search
• Rounding Data and Dynamic Programming
• Deterministic Rounding of Linear Programs (LPs)
• Random Sampling and Randomized Rounding of LPs
• Primal-Dual Methods
• Hardness of Approximation
• Problem Solving under Uncertainty

Dr. Felix Christian Hommelsheim
03-M-SP-12High-Performance-Visualisierung (in englischer Sprache)
High-Performance Visualization
Interaktive Exploration zur Analyse von extrem großen wissenschaftlichen Daten

Vorlesung
ECTS: 4,5 / 6

Termine:
wöchentlich Do 14:00 - 16:00 MZH 1110 Lecture and Exercise

Einzeltermine:
Do 11.07.24 14:00 - 18:00 MZH 1110
Do 22.08.24 - Fr 23.08.24 (Do, Fr) 08:00 - 14:00 MZH 5500

The lecture addresses Interactive Visualization of Huge Scientific Datasets. More information can also be found on the Homepage: https://www.uni-bremen.de/ag-high-performance-visualization

Die Vorlesung beschäftigt sich mit den mathematischen Grundlagen der wissenschaftlichen Visualisierung und behandelt Methoden für das parallele Post-Processing großer wissenschaftlicher Datensätze. Anwendungsbeispiele werden anhand der Open-Source-Software ParaView erläutert.
Homepage zur Veranstaltung: https://www.uni-bremen.de/ag-high-performance-visualization

Prof. Dr. Andreas Gerndt
03-M-SP-14Scientific Programming and Advanced Numerical Methods - an Introduction with Case Studies (in englischer Sprache)

Vorlesung
ECTS: 9

Termine:
wöchentlich Mi 14:00 - 16:00 MZH 2340 Lecture
wöchentlich Do 12:00 - 14:00 MZH 2340 Lecture

Einzeltermine:
Mi 10.07.24 14:00 - 16:00 ZOOM
Mi 17.07.24 14:00 - 16:00 ZOOM
Mo 22.07.24 - Fr 26.07.24 (Mo, Di, Mi, Do, Fr) 10:00 - 16:30

This course provides an introduction to the practice of scientific programming.

Alfred Schmidt
Prof. Dr. Stephan Frickenhaus
03-M-SP-16Mathematical Foundations of Machine Learning (in englischer Sprache)

Vorlesung
ECTS: 9

Termine:
wöchentlich Mo 12:00 - 14:00 MZH 2340 Lecture
wöchentlich Di 12:00 - 14:00 MZH 2340 Lecture
wöchentlich Di 14:00 - 16:00 MZH 2340 Exercise

This course deals with the mathematical foundations of machine learning with a strong focus on classical theory and well-established algorithms like, for example, support vector machines for classification, ridge regression, principal component analysis for dimensionality reduction and k-means clustering. In addition, deep learning with neural networks will be briefly discussed towards the end of the course.

Peter Maaß
Dr. Matthias Beckmann
03-M-SP-20Digital Optimal Control and Optimal Feedback Control (in englischer Sprache)

Vorlesung
ECTS: 9

Termine:
wöchentlich Mo 10:00 - 12:00 Externer Ort: NEOS Gebäude 3. Etage Lecture
wöchentlich Do 10:00 - 12:00 Externer Ort: NEOS Gebäude 3. Etage Lecture
wöchentlich Do 12:00 - 14:00 Externer Ort: NEOS Gebäude 3. Etage Exercise

Die Veranstaltung findet im NEOS Gebäude statt.

Prof. Dr. Christof Büskens
03-M-SP-32Spectral Theory (in englischer Sprache)

Vorlesung
ECTS: 9

Termine:
wöchentlich Mi 14:00 - 16:00 MZH 4140 Lecture
wöchentlich Do 10:00 - 12:00 MZH 4140 Lecture
wöchentlich Do 16:00 - 18:00 MZH 4140 Exercise
PD Dr. Hendrik Vogt
03-M-SP-34Differential Geometry (in englischer Sprache)

Vorlesung
ECTS: 9

Termine:
wöchentlich Di 10:00 - 12:00 MZH 1110 MZH 4140 Lecture
wöchentlich Di 12:00 - 14:00 MZH 1470 Exercise
wöchentlich Mi 16:00 - 18:00 MZH 4140 Lecture

This course will cover manifolds, vector bundles, embeddings and submersions, integral curves and flows, basics of Lie groups, differential forms and integration, Riemannian metrics, geodesics, connections, curvature, and further topics.

Prof. Dr. Anke Dorothea Pohl
03-M-SP-35Selected Topics in Convex Optimization (in englischer Sprache)

Vorlesung
ECTS: 9

Termine:
wöchentlich Mo 10:00 - 12:00 MZH 2340 Lecture
wöchentlich Mi 10:00 - 12:00 MZH 2340 Lecture
wöchentlich Mi 12:00 - 14:00 MZH 2490 (Seminarraum) Exercise

The course will discuss convex optimisation problems and present and analyse algorithms that solve them. Topics will include proximal splitting, acceleration, stochastic algorithms, and performance estimation.

Sebastian Banert
Dirk Lorenz
03-M-SP-36Selected Topics on Optimization for Machine Learning (in englischer Sprache)

Vorlesung
ECTS: 9

Termine:
wöchentlich Do 14:00 - 16:00 MZH 2340 Lecture
wöchentlich Fr 10:00 - 12:00 MZH 2340 Lecture
wöchentlich Fr 12:00 - 14:00 MZH 2340 Exercise
Dirk Lorenz
Lionel Ngoupeyou Tondji

Area of Focus: Industrial Mathematics (45 CP)

Area of Focus (27 CP)

The modules Special Topics Industrial Mathematics A and Special Topics Industrial Mathematics B (9 CP each) are mandatory. In addition, EITHER the module Special Topics Industrial Mathematics C OR the module Advanced Communications Industrial Mathematics (9 CP each) must be studied.

Module: Advanced Communications Industrial Mathematics (2 x 4,5 CP = 9 CP)

Compulsory module in which you must attend a total of two seminars with 4,5 CP each. This semester you can choose from the following seminars:
VAKTitel der VeranstaltungDozentIn
03-M-AC-21Deep Learning for Inverse Problems (in englischer Sprache)

Seminar
ECTS: 4,5/6

Termine:
wöchentlich Mo 14:00 - 16:00 MZH 2340 Seminar
Peter Maaß
03-M-AC-22Advanced Communication Analysis (in englischer Sprache)

Seminar
ECTS: 4,5/6

Termine:
wöchentlich Mi 12:00 - 14:00 MZH 4140 Seminar

Einzeltermine:
Fr 24.05.24 12:00 - 16:00 MZH 1380/1400

In the Seminar Analysis advanced topics in the area of analysis are discussed. The precise topic for Summer semester 2024 will be decided upon with the participants

Prof. Dr. Anke Dorothea Pohl
03-M-AC-23Advanced Robust Control (in englischer Sprache)

Seminar
ECTS: 4,5 / 6

Termine:
wöchentlich Do 10:00 - 12:00 MZH 2340 Seminar
Dr. Chathura Wanigasekara
03-M-AC-28Advanced Numerical Methods for Partial Differential Equations (in englischer Sprache)

Seminar
ECTS: 4,5 / 6

Termine:
wöchentlich Mo 16:00 - 18:00 MZH 2340 Seminar

Seminar on advanced numerical methods for partial differential equations

Alfred Schmidt

Modules: Special Topics Industrial Mathematics (A, B, and C with 9 CP each)

Compulsory modules in which you must attend one lecture each. This semester you can choose from the following lectures:
VAKTitel der VeranstaltungDozentIn
03-IMAT-APX (03-ME-602.99a)Approximation Algorithms (in englischer Sprache)

Kurs
ECTS: 6

Termine:
wöchentlich Di 10:00 - 12:00 MZH 3150 Kurs
wöchentlich Do 14:00 - 16:00 MZH 1470 MZH 5500 Übung

Profil: SQ, KIKR.
Schwerpunkt: IMA-SQ, IMVT-AI, IMVT-VMC
weitere Studiengänge: M-M-Alg-Num, M-T
https://lvb.informatik.uni-bremen.de/imat/03-imat-apx.pdf

A large number of problems arising in practical scenarios like communication, transportation, planning, logistics etc. can be modeled as combinatorial optimization problems. In most cases, these problems are computationally intractable and one often resorts to heuristics that provide sufficiently good solutions in reasonable amount of runtime. However, in most cases, such heuristics do not provide a worst case guarantee on the performance in comparison to the optimum solution. In this course, we shall study algorithms for combinatorial optimization problems which can provide strong mathematical guarantees on performance. The course aims at developing a toolkit for solving such problems. The lectures will consist of designing polynomial-time algorithms and proving rigorous bounds on their worst case performances.
We review many classical results in the field of approximation algorithms, highlighting different techniques commonly used for the design of such algorithms. Among others, we will treat the following topics:
• Greedy algorithms and Local Search
• Rounding Data and Dynamic Programming
• Deterministic Rounding of Linear Programs (LPs)
• Random Sampling and Randomized Rounding of LPs
• Primal-Dual Methods
• Hardness of Approximation
• Problem Solving under Uncertainty

Dr. Felix Christian Hommelsheim
03-M-SP-12High-Performance-Visualisierung (in englischer Sprache)
High-Performance Visualization
Interaktive Exploration zur Analyse von extrem großen wissenschaftlichen Daten

Vorlesung
ECTS: 4,5 / 6

Termine:
wöchentlich Do 14:00 - 16:00 MZH 1110 Lecture and Exercise

Einzeltermine:
Do 11.07.24 14:00 - 18:00 MZH 1110
Do 22.08.24 - Fr 23.08.24 (Do, Fr) 08:00 - 14:00 MZH 5500

The lecture addresses Interactive Visualization of Huge Scientific Datasets. More information can also be found on the Homepage: https://www.uni-bremen.de/ag-high-performance-visualization

Die Vorlesung beschäftigt sich mit den mathematischen Grundlagen der wissenschaftlichen Visualisierung und behandelt Methoden für das parallele Post-Processing großer wissenschaftlicher Datensätze. Anwendungsbeispiele werden anhand der Open-Source-Software ParaView erläutert.
Homepage zur Veranstaltung: https://www.uni-bremen.de/ag-high-performance-visualization

Prof. Dr. Andreas Gerndt
03-M-SP-14Scientific Programming and Advanced Numerical Methods - an Introduction with Case Studies (in englischer Sprache)

Vorlesung
ECTS: 9

Termine:
wöchentlich Mi 14:00 - 16:00 MZH 2340 Lecture
wöchentlich Do 12:00 - 14:00 MZH 2340 Lecture

Einzeltermine:
Mi 10.07.24 14:00 - 16:00 ZOOM
Mi 17.07.24 14:00 - 16:00 ZOOM
Mo 22.07.24 - Fr 26.07.24 (Mo, Di, Mi, Do, Fr) 10:00 - 16:30

This course provides an introduction to the practice of scientific programming.

Alfred Schmidt
Prof. Dr. Stephan Frickenhaus
03-M-SP-16Mathematical Foundations of Machine Learning (in englischer Sprache)

Vorlesung
ECTS: 9

Termine:
wöchentlich Mo 12:00 - 14:00 MZH 2340 Lecture
wöchentlich Di 12:00 - 14:00 MZH 2340 Lecture
wöchentlich Di 14:00 - 16:00 MZH 2340 Exercise

This course deals with the mathematical foundations of machine learning with a strong focus on classical theory and well-established algorithms like, for example, support vector machines for classification, ridge regression, principal component analysis for dimensionality reduction and k-means clustering. In addition, deep learning with neural networks will be briefly discussed towards the end of the course.

Peter Maaß
Dr. Matthias Beckmann
03-M-SP-20Digital Optimal Control and Optimal Feedback Control (in englischer Sprache)

Vorlesung
ECTS: 9

Termine:
wöchentlich Mo 10:00 - 12:00 Externer Ort: NEOS Gebäude 3. Etage Lecture
wöchentlich Do 10:00 - 12:00 Externer Ort: NEOS Gebäude 3. Etage Lecture
wöchentlich Do 12:00 - 14:00 Externer Ort: NEOS Gebäude 3. Etage Exercise

Die Veranstaltung findet im NEOS Gebäude statt.

Prof. Dr. Christof Büskens
03-M-SP-32Spectral Theory (in englischer Sprache)

Vorlesung
ECTS: 9

Termine:
wöchentlich Mi 14:00 - 16:00 MZH 4140 Lecture
wöchentlich Do 10:00 - 12:00 MZH 4140 Lecture
wöchentlich Do 16:00 - 18:00 MZH 4140 Exercise
PD Dr. Hendrik Vogt
03-M-SP-34Differential Geometry (in englischer Sprache)

Vorlesung
ECTS: 9

Termine:
wöchentlich Di 10:00 - 12:00 MZH 1110 MZH 4140 Lecture
wöchentlich Di 12:00 - 14:00 MZH 1470 Exercise
wöchentlich Mi 16:00 - 18:00 MZH 4140 Lecture

This course will cover manifolds, vector bundles, embeddings and submersions, integral curves and flows, basics of Lie groups, differential forms and integration, Riemannian metrics, geodesics, connections, curvature, and further topics.

Prof. Dr. Anke Dorothea Pohl
03-M-SP-35Selected Topics in Convex Optimization (in englischer Sprache)

Vorlesung
ECTS: 9

Termine:
wöchentlich Mo 10:00 - 12:00 MZH 2340 Lecture
wöchentlich Mi 10:00 - 12:00 MZH 2340 Lecture
wöchentlich Mi 12:00 - 14:00 MZH 2490 (Seminarraum) Exercise

The course will discuss convex optimisation problems and present and analyse algorithms that solve them. Topics will include proximal splitting, acceleration, stochastic algorithms, and performance estimation.

Sebastian Banert
Dirk Lorenz
03-M-SP-36Selected Topics on Optimization for Machine Learning (in englischer Sprache)

Vorlesung
ECTS: 9

Termine:
wöchentlich Do 14:00 - 16:00 MZH 2340 Lecture
wöchentlich Fr 10:00 - 12:00 MZH 2340 Lecture
wöchentlich Fr 12:00 - 14:00 MZH 2340 Exercise
Dirk Lorenz
Lionel Ngoupeyou Tondji

Extension (18 CP)

Module: Advanced Communications Data Analysis (2 x 4,5 CP = 9 CP)

Compulsory module in which you must attend a total of two seminars with 4,5 CP each. This semester you can choose from the following seminars:
VAKTitel der VeranstaltungDozentIn
03-M-AC-21Deep Learning for Inverse Problems (in englischer Sprache)

Seminar
ECTS: 4,5/6

Termine:
wöchentlich Mo 14:00 - 16:00 MZH 2340 Seminar
Peter Maaß
03-M-AC-22Advanced Communication Analysis (in englischer Sprache)

Seminar
ECTS: 4,5/6

Termine:
wöchentlich Mi 12:00 - 14:00 MZH 4140 Seminar

Einzeltermine:
Fr 24.05.24 12:00 - 16:00 MZH 1380/1400

In the Seminar Analysis advanced topics in the area of analysis are discussed. The precise topic for Summer semester 2024 will be decided upon with the participants

Prof. Dr. Anke Dorothea Pohl
03-M-AC-23Advanced Robust Control (in englischer Sprache)

Seminar
ECTS: 4,5 / 6

Termine:
wöchentlich Do 10:00 - 12:00 MZH 2340 Seminar
Dr. Chathura Wanigasekara
03-M-AC-28Advanced Numerical Methods for Partial Differential Equations (in englischer Sprache)

Seminar
ECTS: 4,5 / 6

Termine:
wöchentlich Mo 16:00 - 18:00 MZH 2340 Seminar

Seminar on advanced numerical methods for partial differential equations

Alfred Schmidt

Module: Special Topics Data Analysis A (9 CP)

Compulsory module in which you must attend one lecture. This semester you can choose from the following lectures:
VAKTitel der VeranstaltungDozentIn
03-M-SP-12High-Performance-Visualisierung (in englischer Sprache)
High-Performance Visualization
Interaktive Exploration zur Analyse von extrem großen wissenschaftlichen Daten

Vorlesung
ECTS: 4,5 / 6

Termine:
wöchentlich Do 14:00 - 16:00 MZH 1110 Lecture and Exercise

Einzeltermine:
Do 11.07.24 14:00 - 18:00 MZH 1110
Do 22.08.24 - Fr 23.08.24 (Do, Fr) 08:00 - 14:00 MZH 5500

The lecture addresses Interactive Visualization of Huge Scientific Datasets. More information can also be found on the Homepage: https://www.uni-bremen.de/ag-high-performance-visualization

Die Vorlesung beschäftigt sich mit den mathematischen Grundlagen der wissenschaftlichen Visualisierung und behandelt Methoden für das parallele Post-Processing großer wissenschaftlicher Datensätze. Anwendungsbeispiele werden anhand der Open-Source-Software ParaView erläutert.
Homepage zur Veranstaltung: https://www.uni-bremen.de/ag-high-performance-visualization

Prof. Dr. Andreas Gerndt
03-M-SP-15Analytic and Discrete Convex Geometry (in englischer Sprache)

Vorlesung
ECTS: 9

Termine:
wöchentlich Mo 12:00 - 14:00 MZH 4140 Lecture
wöchentlich Mi 10:00 - 12:00 MZH 1100 MZH 5220 (Didaktik-Labor) Lecture
wöchentlich Mi 12:00 - 14:00 MZH 3150 Exercise

Convex Geometry plays an essential role in several branches of Mathematics, from Discrete Mathematics to Harmonic Analysis. We will discuss some major analytic and discrete aspects of convex geometry and some applications. Our topics will range from the boundary structure of convex bodies, particularly polytopes, to Hadwiger's volume characterisation, via geometric and functional inequalities, as well as geometric and analytic symmetrization techniques.

Eugenia Saorin Gomez
03-M-SP-16Mathematical Foundations of Machine Learning (in englischer Sprache)

Vorlesung
ECTS: 9

Termine:
wöchentlich Mo 12:00 - 14:00 MZH 2340 Lecture
wöchentlich Di 12:00 - 14:00 MZH 2340 Lecture
wöchentlich Di 14:00 - 16:00 MZH 2340 Exercise

This course deals with the mathematical foundations of machine learning with a strong focus on classical theory and well-established algorithms like, for example, support vector machines for classification, ridge regression, principal component analysis for dimensionality reduction and k-means clustering. In addition, deep learning with neural networks will be briefly discussed towards the end of the course.

Peter Maaß
Dr. Matthias Beckmann
03-M-SP-22Linear and Generalized Linear Regression (Statistics II) (in englischer Sprache)

Vorlesung
ECTS: 9

Termine:
wöchentlich Mi 08:00 - 10:00 MZH 7200 Lecture
wöchentlich Mi 10:00 - 12:00 MZH 7200 Exercise
wöchentlich Do 08:00 - 10:00 MZH 7200 Lecture

Einzeltermine:
Do 25.07.24 10:00 - 12:00 MZH 7200
Maryam Movahedifar
03-M-SP-33Semiparametric Models (in englischer Sprache)

Vorlesung
ECTS: 9

Termine:
wöchentlich Di 09:00 - 10:30 Vorlesung
wöchentlich Mi 14:00 - 16:00 Übung
wöchentlich Fr 12:30 - 14:00 Vorlesung

Die Veranstaltung findet im KKSB statt.

The course will provide an introduction into the theory of semiparametric models. We will introduce and discuss the mathematical statistical theory for such models and will illustrate the utility of semiparametric models with a number of concrete models and data examples. Hence, the lecture and exercises will cover theoretical and practical aspects of semiparametric models. We will use the open statistical software R for the data applications.

Prof. Dr. Werner Brannath
03-M-SP-34Differential Geometry (in englischer Sprache)

Vorlesung
ECTS: 9

Termine:
wöchentlich Di 10:00 - 12:00 MZH 1110 MZH 4140 Lecture
wöchentlich Di 12:00 - 14:00 MZH 1470 Exercise
wöchentlich Mi 16:00 - 18:00 MZH 4140 Lecture

This course will cover manifolds, vector bundles, embeddings and submersions, integral curves and flows, basics of Lie groups, differential forms and integration, Riemannian metrics, geodesics, connections, curvature, and further topics.

Prof. Dr. Anke Dorothea Pohl
03-M-SP-35Selected Topics in Convex Optimization (in englischer Sprache)

Vorlesung
ECTS: 9

Termine:
wöchentlich Mo 10:00 - 12:00 MZH 2340 Lecture
wöchentlich Mi 10:00 - 12:00 MZH 2340 Lecture
wöchentlich Mi 12:00 - 14:00 MZH 2490 (Seminarraum) Exercise

The course will discuss convex optimisation problems and present and analyse algorithms that solve them. Topics will include proximal splitting, acceleration, stochastic algorithms, and performance estimation.

Sebastian Banert
Dirk Lorenz
03-M-SP-36Selected Topics on Optimization for Machine Learning (in englischer Sprache)

Vorlesung
ECTS: 9

Termine:
wöchentlich Do 14:00 - 16:00 MZH 2340 Lecture
wöchentlich Fr 10:00 - 12:00 MZH 2340 Lecture
wöchentlich Fr 12:00 - 14:00 MZH 2340 Exercise
Dirk Lorenz
Lionel Ngoupeyou Tondji

Industriemathematik, B.Sc.

General Studies - Fachergänzende Studien

Fachergänzendes Studienangebot aus der Mathematik bzw. Industriemathematik.
VAKTitel der VeranstaltungDozentIn
03-IBFW-HTO (03-BE-699.12)Hands-on Tutorial on Optimization (in englischer Sprache)

Blockveranstaltung
ECTS: 3

Einzeltermine:
Mo 23.09.24 - Fr 27.09.24 (Mo, Di, Mi, Do, Fr) 09:00 - 17:00 MZH 5500

https://lvb.informatik.uni-bremen.de/igs/03-ibfw-hto.pdf
A large number of problems arising in practical scenarios like communication, transportation, planning, logistics etc. can be formulated as discrete linear optimization problems. This course briefly introduces the theory of such problems. We develop a toolkit to model real-world problems as (discrete) linear programs. We also explore several ways to find integer solutions such as cutting planes, branch & bound, and column generation.

Throughout the course, we learn these skills by modeling and solving, for example, scheduling, packing, matching, routing, and network-design problems. We focus on translating practical examples into mixed-integer linear programs. We learn how to use solvers (such as CPLEX and Gurobi) and tailor the solution process to certain properties of the problem.

This course consists of two phases:

  • One week Mon-Fri (full day, 9-5) of lectures and practical labs: September 23-27, in MZH.
  • A subsequent project period: One problem has to be modeled, implemented, and solved individually or in a group of at most three students. The topic will be provided by the lecturers and will be discussed on the last day of the block course. The project including the implementation has to be presented in the beginning of the winter semester.

There are no prerequisites except some basic programming skills to participate.

Prof. Dr. Nicole Megow
03-M-GS-7Introduction to R (in englischer Sprache)

Vorlesung
ECTS: 3

Termine:
wöchentlich Fr 10:00 - 13:00 GW1 A0150 Seminar

3 SWS Seminar
Raum wird nach Anmeldung in Stud.IP bekannt gegeben.
Homepage des KKSB und Uni-Lageplan

Prof. Dr. Werner Brannath
Eike Voß
SZHB 0622ONLINE: English for Mathematicians and Industrial Mathematicians (Zertifikatskurs UNIcert II) (B2.3) (in englischer Sprache)
Eingangsniveau: B2.2

Kurs
ECTS: 3

Termine:
wöchentlich Di 16:15 - 17:55 Externer Ort: Onlinekurs (2 SWS)


Edwin Shillington

Informatik, B.Sc./M.Sc.

Bachelor Informatik

Wahlbereich Bachelor-Aufbau (IBA) / Bachelor-Basis (BB)

IBAP / BB-7: Praktische und Technische Informatik

Nach BPO 2020 mindestens ein Lehrangebot aus dieser Kategorie wählen.
Für ,,Bachelor - PrakTechInfWahl`` zwei Module aus dieser Kategorie wählen: BB-7xx.xx. Keine Ausnahmeanträge.
VAKTitel der VeranstaltungDozentIn
03-IBAP-ML (03-BB-710.10)Grundlagen des Maschinellen Lernens (in englischer Sprache)
Fundamentals of Machine Learning

Kurs
ECTS: 6

Termine:
wöchentlich Mo 14:00 - 16:00 MZH 1470 Übung
wöchentlich Mi 08:00 - 10:00 MZH 1380/1400 Vorlesung
wöchentlich Mi 10:00 - 12:00 MZH 1380/1400 GW2 B1820 Übung

Einzeltermine:
Mi 12.06.24 08:00 - 09:30 MZH 1380/1400
Di 23.07.24 14:00 - 16:00 NW1 H 1 - H0020

Schwerpunkt: AI
https://lvb.informatik.uni-bremen.de/ibap/03-ibap-ml.pdf
Die Übungen starten in der 2. Semesterwoche.

Tanja Schultz
Felix Putze
Darius Ivucic
Gabriel Ivucic
Zhao Ren
03-IBAP-MRCAModern Robot Control Architectures (in englischer Sprache)

Vorlesung
ECTS: 6

Termine:
wöchentlich Mo 10:00 - 12:00 DFKI RH1 B0.10 Vorlesung
wöchentlich Do 14:00 - 16:00 DFKI RH1 B0.10 Übung

https://lvb.informatik.uni-bremen.de/ibap/03-ibap-mrca.pdf
Robotics is a complex field that emerged at the intersection of multiple disciplines such as physics, mathematics and computer science. New advances in hardware and software design and progress in artificial intelligence enable robotics research to pursue higher goals and achieve increased autonomy in various environments. For instance, robots can operate in disaster zones for search and rescue operations, can be employed in rehabilitation and healthcare, space and underwater exploration, etc. Given the complexity of such scenarios, it is essential to develop robust robotic systems with a high degree of autonomy, able to assist humans in difficult and tedious tasks.

This course aims to provide the fundamentals of modern robot control approaches that enable robotic agents to operate in the environment autonomously. The course introduces a basic understanding of autonomous robots, along with tools and methods to control various types of mobile robotic platforms and manipulators. Firstly, the course presents the types of sensors and actuators employed in autonomous robotic platforms. Secondly, it offers a formal understanding of the robot geometry, its kinematic and dynamic models. Finally, the course provides methods and approaches to control the robotic system from a deliberative and reactive point of view. Students will put this knowledge into practice during tutorials and exercise sheets using Python implementation and robot simulations.

Contents

  • Introduction to Robotics and AI: long term robot autonomy, artificial intelligence, deliberative vs. reactive control, robotic applications.
  • Sensing and Actuation Modalities: types of sensors and actuators, sensor fusion, actuator control.
  • Robot Geometry and Transformations: robot transformations in the 3D space, exponential and logarithmic maps, forward and inverse geometric models.
  • Kinematics: definition of twists and wrenches for rigid bodies, geometric Jacobian formulation, forward and inverse kinematics.
  • Dynamics: an introduction to Lagrangian and Newtonian mechanics, robot dynamics formulation, recursive Newton-Euler algorithm.
  • Localization: direct and probabilistic methods for robot localization, odometry, global localization, particle filter.
  • Path Planning: path vs. trajectory generation, graph-based methods for path planning (e.g. Djikstra, A\*).
  • Kinodynamic Planning: transcribing a dynamic planning problem into trajectory optimization, direct and indirect methods, costs and constraints.
  • Reinforcement Learning-based Control: mathematical foundations, discrete vs continuous methods, reinforcement learning for closed-loop robot control.
  • Dynamic Control: PD gravity compensation control, computed torque control, admittance vs impedance control.
  • Optimal Control: energy-shaping control, LQR and time-varying LQR control.

Learning Outcomes

At the end of the course, the student is expected to be able to:
  • Define robot autonomy and list its key aspects.
  • Describe the sensor and actuator modalities used in robotics, and explain their relevance for robot control.
  • Implement and understand the low-level actuator control methods.
  • Compute the 3D world coordinate transformations for rigid bodies.
  • Apply the robot forward and inverse geometric model.
  • Describe a robotic system based on its kinematic and dynamic properties.
  • Use probabilistic methods for robot localization.
  • Generate an optimal path for a mobile robot or manipulator using graph search methods.
  • Plan a path taking into account the robot kinodynamic properties.
  • Use reinforcement learning methods to control simple robotic systems.
  • Apply dynamical and optimal control methods on robotic systems such that they are robust against disturbances.
  • Assess the strengths and limitations of different control methods presented in the course.
  • Identify open challenges in robotics research and current trends in state-of-the-art.
  • Communicate confidently using the terminology in the field of robotics.
  • Cooperate and work in teams in order to solve tasks.

Examination

During the semester, students are required to complete 6 worksheets in groups of 4.
To pass the course, students must achieve a minimum of 50% on both the worksheets and the written exam.
The final grade is 40% based on worksheets and 60% on the written exam.

References

  • Mechanics of Robotic Manipulation, Mathew T. Masen, MIT press, 2001.
  • Algebra and Geometry, Alan F. Beardon, Cambridge University Press, 2005.
  • Modelling and Control of Robot Manipulators, Lorenzo Sciavicco, Bruno Siciliano, Springer, 2000.
  • Probabilistic Robotics (Intelligent Robotics and Autonomous Agents), Sebastian Thrun, Wolfram Burgard, and Dieter Fox, MIT Press, 2005.
  • Introduction to Autonomous Mobile Robots, Siegwart R., Nourbakhsh I., Scaramuzza D., MIT press, 2011.
  • Automated Planning: Theory and Practice, Malik Ghallab, Dana Nau, Paolo Traverso, Elsevier, 2004.
  • Behaviour-based robotics, R. C. Arkin, MIT press, 1998.
  • Modern Robotics: Mechanics, Planning, and Control, Kevin M. Lynch and Frank C. Park, Cambridge University Press, 2017.

Frank Kirchner
M. Sc. Mihaela Popescu (Organizer)
M. Sc Jonas Haack

Wahlbereich Bachelor-Vertiefung (IBV) / Bachelor-Ergänzung (BE)

Weitere Wahlangebote können aus dem Wahlbreich IBA/BB und bei Vorliegen der inhaltlichen Voraussetzungen aus dem Wahlangebot des Masterstudiengangs Informatik gewählt werden.
BPO \'10: weitere BE-Angebote unter Wahlbereich IBFW
BPO\'20: nur IBA/IBV

IBVT / BE-6: Theoretische Informatik und Mathematik

VAKTitel der VeranstaltungDozentIn
03-M-GS-7Introduction to R (in englischer Sprache)

Vorlesung
ECTS: 3

Termine:
wöchentlich Fr 10:00 - 13:00 GW1 A0150 Seminar

3 SWS Seminar
Raum wird nach Anmeldung in Stud.IP bekannt gegeben.
Homepage des KKSB und Uni-Lageplan

Prof. Dr. Werner Brannath
Eike Voß

IBVP / BE-7: Praktische und Technische Informatik

VAKTitel der VeranstaltungDozentIn
IBVP-AKRActionable Knowledge Representation (in englischer Sprache)

Vorlesung
ECTS: 6

Termine:
wöchentlich Di 10:00 - 12:00 Vorlesung
wöchentlich Di 12:00 - 14:00 Übung

Die Veranstaltung findet im TAB in Raum 0.30 statt.
https://lvb.informatik.uni-bremen.de/ibv/03-ibvp-akr.pdf

This course deals with the idea of bringing knowledge into applications to support users in daily life. It therefore covers topics on how knowledge can be represented to be machine-understandable, how knowledge can be acquired from different sources (including Web scraping) and how such different knowledge chunks can be linked. It will further discuss how to reason about knowledge and how different agents like websites, AR applications or robots can use knowledge to support users in their daily life. All exercises will be available in platform-independent jupyter notebooks based on python and have low software requirements.

Robert Porzel
Michaela Kümpel

IBVA / BE-8: Angewandte Informatik

VAKTitel der VeranstaltungDozentIn
03-IBVA-DSV (03-BE-802.98a)Data Science and Visualization (in englischer Sprache)

Kurs
ECTS: 6

Termine:
wöchentlich Mo 10:00 - 12:00 MZH 5600 Kurs
wöchentlich Mo 12:00 - 14:00 MZH 5600 Kurs

Eine Doppelanerkennung von 'Data Science' und 'Data Science and Visualization' ist nicht möglich.
https://lvb.informatik.uni-bremen.de/ibv/03-ibva-dsv.pdf

The class will provide an introduction to data science and information visualization. For this, the programming language Python will be used (and taught). For creating data visualizations, you will be able to choose among a series of tools (e.g., Plotly, Observable, etc.)

We will explore different concepts from the fields of human-computer interaction, data visualization, and computer-supported collaborative work. You will learn about:
      • Basic statistics
      • Visualization techniques
      • Interaction design
Exploratory data analysis and evaluation, as an integral part of data science, will also be taught. The course will involve applying the learned techniques to real-world datasets to develop a custom project.

This class is taught in person and in English. Use material like the coursebook to learn more about the topics as we progress in the course.

Dr. Gabriela Molina Leon

Freie Wahl inkl. Seminare - IBFW / BE

Informationen zum Thema General Studies findet ihr auch hier: https://www.szi.uni-bremen.de/wp-content/uploads/2021/10/GSListe.pdf
VAKTitel der VeranstaltungDozentIn
03-IBFW-HTO (03-BE-699.12)Hands-on Tutorial on Optimization (in englischer Sprache)

Blockveranstaltung
ECTS: 3

Einzeltermine:
Mo 23.09.24 - Fr 27.09.24 (Mo, Di, Mi, Do, Fr) 09:00 - 17:00 MZH 5500

https://lvb.informatik.uni-bremen.de/igs/03-ibfw-hto.pdf
A large number of problems arising in practical scenarios like communication, transportation, planning, logistics etc. can be formulated as discrete linear optimization problems. This course briefly introduces the theory of such problems. We develop a toolkit to model real-world problems as (discrete) linear programs. We also explore several ways to find integer solutions such as cutting planes, branch & bound, and column generation.

Throughout the course, we learn these skills by modeling and solving, for example, scheduling, packing, matching, routing, and network-design problems. We focus on translating practical examples into mixed-integer linear programs. We learn how to use solvers (such as CPLEX and Gurobi) and tailor the solution process to certain properties of the problem.

This course consists of two phases:

  • One week Mon-Fri (full day, 9-5) of lectures and practical labs: September 23-27, in MZH.
  • A subsequent project period: One problem has to be modeled, implemented, and solved individually or in a group of at most three students. The topic will be provided by the lecturers and will be discussed on the last day of the block course. The project including the implementation has to be presented in the beginning of the winter semester.

There are no prerequisites except some basic programming skills to participate.

Prof. Dr. Nicole Megow

Master Informatik

Wahlbereich Master-Aufbau (IMA) / Master-Basis (MB)

Nach der Prüfunsordnung von 2020 heißt dieser Bereich Master-Aufbau (IMA), nach der Prüfungsordnung von 2012 Master-Basis (MB).

IMAT / MB-6 - Theoretische Informatik und Mathematik

Nach MPO 2020 und MPO 2012 mindestens ein Lehrangebot aus dieser Kategorie wählen.
Nach MPO 2012 auf Antrag auch ME-6xx.xx-Lehrangebot oder fortgeschrittenes Mathematik-Lehrangebot möglich.
VAKTitel der VeranstaltungDozentIn
03-IMAT-APX (03-ME-602.99a)Approximation Algorithms (in englischer Sprache)

Kurs
ECTS: 6

Termine:
wöchentlich Di 10:00 - 12:00 MZH 3150 Kurs
wöchentlich Do 14:00 - 16:00 MZH 1470 MZH 5500 Übung

Profil: SQ, KIKR.
Schwerpunkt: IMA-SQ, IMVT-AI, IMVT-VMC
weitere Studiengänge: M-M-Alg-Num, M-T
https://lvb.informatik.uni-bremen.de/imat/03-imat-apx.pdf

A large number of problems arising in practical scenarios like communication, transportation, planning, logistics etc. can be modeled as combinatorial optimization problems. In most cases, these problems are computationally intractable and one often resorts to heuristics that provide sufficiently good solutions in reasonable amount of runtime. However, in most cases, such heuristics do not provide a worst case guarantee on the performance in comparison to the optimum solution. In this course, we shall study algorithms for combinatorial optimization problems which can provide strong mathematical guarantees on performance. The course aims at developing a toolkit for solving such problems. The lectures will consist of designing polynomial-time algorithms and proving rigorous bounds on their worst case performances.
We review many classical results in the field of approximation algorithms, highlighting different techniques commonly used for the design of such algorithms. Among others, we will treat the following topics:
• Greedy algorithms and Local Search
• Rounding Data and Dynamic Programming
• Deterministic Rounding of Linear Programs (LPs)
• Random Sampling and Randomized Rounding of LPs
• Primal-Dual Methods
• Hardness of Approximation
• Problem Solving under Uncertainty

Dr. Felix Christian Hommelsheim

IMAP / MB-7 - Praktische und technische Informatik

Nach MPO 2020 mindestens ein Lehrangebot aus dieser Kategorie wählen. Nach MPO 2012 zwei Lehrangebote aus dieser Kategorie wählen.
VAKTitel der VeranstaltungDozentIn
03-IMAP-AMLAdvanced Machine Learning (in englischer Sprache)

Vorlesung
ECTS: 6

Termine:
wöchentlich Mo 10:00 - 12:00 MZH 6200 Übung
wöchentlich Di 16:00 - 18:00 MZH 1450 Übung
wöchentlich Mi 14:00 - 16:00 MZH 1380/1400 Vorlesung

Profil: KIKR
Schwerpunkt: IMAP-AI, IMA-VMC
https://lvb.informatik.uni-bremen.de/imap/03-imap-aml.pdf

Tanja Schultz
Felix Putze
03-IMAP-DIS (03-MB-703.02)Design of Information Systems (in englischer Sprache)

Vorlesung
ECTS: 6

Termine:
wöchentlich Mo 12:00 - 14:00 MZH 1450 Vorlesung
wöchentlich Di 08:00 - 10:00 MZH 1110 Übung

Profil: SQ.
Schwerpunkt: IMVP-DMI, IMVP-SQ
https://lvb.informatik.uni-bremen.de/imap/03-imap-dis.pdf
Die Veranstaltung ist inhaltlich identisch mit "Entwurf von Informationssystemen" (keine Doppelanerkennung möglich).

Martin Gogolla
03-IMAP-RL (03-ME-712.03)Reinforcement Learning (in englischer Sprache)

Kurs
ECTS: 6

Termine:
wöchentlich Di 10:00 - 12:00 DFKI RH1 B0.10 Kurs
wöchentlich Do 16:00 - 18:00 DFKI RH1 B0.10 Kurs

Profil: KIKR.
Schwerpunkt: IMA-AI, IMVP-VMC
https://lvb.informatik.uni-bremen.de/imap/03-imap-rl.pdf

Frank Kirchner
Melvin Laux
03-IMAP-SECOROSoftware Engineering for Cognitive Robots (in englischer Sprache)

Vorlesung
ECTS: 6

Termine:
wöchentlich Di 08:00 - 10:00 MZH 1090 Vorlesung
wöchentlich Mi 14:00 - 16:00 MZH 1090 Übung


Nico Hochgeschwender

IMAA / MB-8 - Angewandte Informatik

Nach MPO 2012 ein Lehrangebot aus dieser Kategorie wählen. Nur nach MPO 2012 auf Antrag auch ME-8xx.xx-Modul möglich.
VAKTitel der VeranstaltungDozentIn
03-IMAA-CTHCICurrent Topics in Human Computer Interaction (in englischer Sprache)

Kurs
ECTS: 6

Termine:
wöchentlich Mi 10:00 - 14:00 SFG 0150 Kurs

Profil: DMI
Schwerpunkt: IMA-DMI, IMA-VMC
https://lvb.informatik.uni-bremen.de/imaa/03-imaa-cthci.pdf

Prof. Dr. Tanja Döring
03-IMAA-EC (03-MB-804.03)Entertainment Computing (in englischer Sprache)

Vorlesung
ECTS: 6

Termine:
wöchentlich Di 10:00 - 12:00 MZH 6200 Vorlesung
wöchentlich Di 12:00 - 14:00 MZH 6200 Übung

Profil: DMI
Schwerpunkt: IMK-DMI, IMA-VMC
https://lvb.informatik.uni-bremen.de/imaa/03-imaa-ec.pdf

Prof. Dr. Rainer Malaka
Rachel Ringe
Leon Tristan Dratzidis
Nima Zargham
03-IMAA-MAD (03-ME-804.06)Mobile App Development (in englischer Sprache)

Vorlesung
ECTS: 6

Termine:
wöchentlich Mo 12:00 - 14:00 MZH 6200 Vorlesung
wöchentlich Mo 14:00 - 16:00 MZH 6200 Übung

Profil: DMI
Schwerpunkt: IMA-DMI, IMVA-DMI
https://lvb.informatik.uni-bremen.de/imva/03-imva-mad.pdf
Die Veranstaltung richtet sich an Studenten der Informatik und Digitalen Medien. In Gruppenarbeit sollen die Studierenden semesterbegleitend ein App-Projekt umsetzen. In der Vorlesung werden alle relevanten Informationen der modernen Softwareentwicklung, mit Fokus auf die mobile App-Entwickung, vermittelt. Dazu gehören Themen wie mobiles Testing, Scrum, UX Design, Evaluation & Nutzertests, Design Patterns und Cross-Plattform-Entwicklung. Das Ziel dabei ist die Vermittlung von praxisrelevantem Wissen aus dem Alltag eines erfolgreichen Unternehmens.

Prof. Dr. Rainer Malaka
David Ruh
Nicolas Autzen

Wahlbereich Master-Vertiefung (IMV) / Master-Ergänzung (ME)

MPO 2012: weitere ME-Angebote unter Wahlbereich IMS/ME und unter General Studies IMGS

IMVT / ME-6 - Theoretische Informatik

VAKTitel der VeranstaltungDozentIn
03-M-SP-12High-Performance-Visualisierung (in englischer Sprache)
High-Performance Visualization
Interaktive Exploration zur Analyse von extrem großen wissenschaftlichen Daten

Vorlesung
ECTS: 4,5 / 6

Termine:
wöchentlich Do 14:00 - 16:00 MZH 1110 Lecture and Exercise

Einzeltermine:
Do 11.07.24 14:00 - 18:00 MZH 1110
Do 22.08.24 - Fr 23.08.24 (Do, Fr) 08:00 - 14:00 MZH 5500

The lecture addresses Interactive Visualization of Huge Scientific Datasets. More information can also be found on the Homepage: https://www.uni-bremen.de/ag-high-performance-visualization

Die Vorlesung beschäftigt sich mit den mathematischen Grundlagen der wissenschaftlichen Visualisierung und behandelt Methoden für das parallele Post-Processing großer wissenschaftlicher Datensätze. Anwendungsbeispiele werden anhand der Open-Source-Software ParaView erläutert.
Homepage zur Veranstaltung: https://www.uni-bremen.de/ag-high-performance-visualization

Prof. Dr. Andreas Gerndt

IMVP / ME-7 - Praktische Informatik

VAKTitel der VeranstaltungDozentIn
03-IMVP-ACAAdvanced Computer Architecture (in englischer Sprache)

Vorlesung
ECTS: 6

Termine:
wöchentlich Mo 08:00 - 10:00 MZH 5600 Vorlesung
wöchentlich Di 08:00 - 10:00 MZH 5600 Übung
Prof. Dr. Rolf Drechsler
Dr. Kamalika Datta
03-IMVP-ECLEdge Computing Lab (in englischer Sprache)

Kurs
ECTS: 6

Termine:
wöchentlich Mo 16:00 - 18:00 MZH 1110 Kurs


Peter Fereed Haddawy
Prof. Dr. Anna Förster
Thomas Dieter Barkowsky
03-IMVP-LSPDLogic Synthesis and Physical Design (in englischer Sprache)

Vorlesung
ECTS: 6

Termine:
wöchentlich Mi 16:00 - 18:00 MZH 1380/1400 Vorlesung
wöchentlich Do 08:00 - 10:00 MZH 1100 Übung


Prof. Dr. Marcel Walter
03-IMVP-MPAR (03-ME-708.05)Massively-Parallel Algorithms (in englischer Sprache)

Vorlesung
ECTS: 6

Termine:
wöchentlich Di 16:00 - 18:00 MZH 1110 Vorlesung
wöchentlich Mi 08:00 - 10:00 MZH 1100 Übung

https://lvb.informatik.uni-bremen.de/imvp/03-imvp-mpar.pdf
Profil: SQ, KIKR, DMI.
Schwerpunkt: SQ, AI, DMI, VMC
Some prior expertise in C will be helpful. The lecture will be held in German or English, depending on demand.
https://cgvr.cs.uni-bremen.de/teaching/

Prof. Dr. Gabriel Zachmann
03-IMVP-TCRSTrustworthy Cognitive Robots and Systems (in englischer Sprache)

Vorlesung
ECTS: 6

Termine:
wöchentlich Mi 12:00 - 14:00 MZH 5600 Vorlesung
wöchentlich Do 10:00 - 12:00 MZH 1450 Übung

Einzeltermine:
Mi 29.05.24 13:00 - 14:00 https://uni-bremen.zoom-x.de/j/67174967283?pwd=U2N4K0F0bnlIUWUwUU1ONGFrZ1NWUT09


Nico Hochgeschwender
03-IMVP-UCNBUnconventional Computing: Nanotech and Biochips (in englischer Sprache)

Vorlesung
ECTS: 6

Termine:
wöchentlich Do 12:00 - 14:00 MZH 1450 Vorlesung
wöchentlich Do 14:00 - 16:00 MZH 1450 Übung


Prof. Dr. Marcel Walter

IMVA / ME-8 - Angewandte Informatik

VAKTitel der VeranstaltungDozentIn
03-IMVA-ACSSApplied Computer Science in Sports (in englischer Sprache)

Kurs
ECTS: 6

Termine:
wöchentlich Mi 14:00 - 18:00 MZH 1110 Kurs

Schwerpunkt: IMVA-AI, IMVA-DMI
https://lvb.informatik.uni-bremen.de/imva/03-imva-acss.pdf
The aim of this course is to create an understanding of the major aspects of sports applications. The course is split into two parts: the first half has a classic lecture/tutorial style, whereas the second half will focus on the creation of individual sports applications.

The lectures will explain the necessary fundamentals, such as sensor technology, user feedback, and the conduction of empirical studies, along with a number of inspiring examples.

In the project part, own prototypes for sports applications are developed in small groups. The exact application as well as the technical implementation approach can be chosen freely. The final graded outcome of the course will be a small sports application about which a presentation has to be held and a documentation in a scientific paper style has to be written.

The course will be held in English.

Schwerpunkt: AI, DMI

Robert Porzel
Dr. Tim Laue
Bastian Dänekas
03-IMVA-DSSDecision Support Systems (in englischer Sprache)

Vorlesung
ECTS: 6

Termine:
wöchentlich Mi 08:15 - 10:00 MZH 1110
wöchentlich Mi 10:00 - 12:00 MZH 1110 Vorlesung und Übung


Dr. Gerhard Klassen
Dr. Marc Wyszynski
Prof. Dr. Dr. Björn Niehaves
Sebastian Weber
Patricia Zauchner
03-IMVA-EI (03-ME-899.03)Embodied Interaction (in englischer Sprache)

Kurs
ECTS: 6

Termine:
wöchentlich Do 08:00 - 10:00 MZH 1110 Kurs
wöchentlich Do 10:00 - 12:00 MZH 1110 Kurs

Profil: DMI.
Schwerpunkt: IMVA-DMI, IMVA-VMC
https://lvb.informatik.uni-bremen.de/imva/03-imva-ei.pdf

Robert Porzel
Prof. Dr. Rainer Malaka
03-IMVA-GACGenerative AI and Creativity - Understanding the Impact on Digital Media (in englischer Sprache)

Kurs
ECTS: 6

Termine:
wöchentlich Mo 12:00 - 14:00 MZH 1470 Kurs
wöchentlich Mi 12:00 - 14:00 MZH 1470 Seminar

4 SWS, Schwerpunkt: IMVA-DMI
https://lvb.informatik.uni-bremen.de/imva/03-imva-gac.pdf

In this seminar, we want to investigate current tools and models (e.g., Dall-E2, ChatGPT) for creating content. We will discuss the idea and design and the implications for artists, developers, and researchers. Therefore, we will read current research papers and develop applications that use these models. We want to design and create new interfaces and ideas to support users with these tools. The course is open to Digital Media and Computer Science students.

Dr. Nina Wenig
03-IMVA-TMPThe Machinic Project (in englischer Sprache)

Seminar
ECTS: 6

Termine:
wöchentlich Mo 10:00 - 12:00 MZH 1450 Seminar
wöchentlich Di 10:00 - 12:00 MZH 1450 Seminar


Dr. Bernhard Robben
Frieder Nake

Wahlbereich IMS / ME - Master Seminare

VAKTitel der VeranstaltungDozentIn
03-DMM-MA-2-ONTHON THINKING. Logic – algorithmic – dialectic (in englischer Sprache)

Seminar
ECTS: 3

Termine:
wöchentlich Di 14:00 - 16:00 MZH 1450 Seminar
Frieder Nake
03-IMS-AISSeminar on Autonomous and Intelligent Systems (in englischer Sprache)

Seminar
ECTS: 3

Termine:
wöchentlich Di 08:00 - 10:00 DFKI RH1 B0.10 Seminar


Frank Kirchner
Melvin Laux
Dr. Lisa Gutzeit
03-IMS-APMSK (03-ME-711.09)Ausgewählte Probleme der multisensorischen Kognition (in englischer Sprache)
Selected Problems of Multisensory Cognition

Seminar
ECTS: 3

Termine:
wöchentlich Do 12:00 - 14:00 CART Rotunde - 0.67 Seminar

Profil: KIKR, DMI.
https://lvb.informatik.uni-bremen.de/ims/03-ims-apmsk.pdf
Die Veranstaltung findet in Englischer Sprache statt.

Christop W. Zetzsche-Schill
Kerstin Schill
03-IMS-CNTComputational Nanotechnologies (in englischer Sprache)

Blockveranstaltung
ECTS: 3

Einzeltermine:
Mi 03.04.24 14:00 - 16:00 MZH 4380 (AGRA-Raum)

Genaue Block-Zeiten werden noch bekanntgegeben.
Der Einführungstermin findet am 03.04.2024 in Raum 4380 statt.

https://lvb.informatik.uni-bremen.de/ims/03-ims-cnt.pdf

Prof. Dr. Marcel Walter
03-IMS-MBCDLMultimodal Biosignal Collection in Daily Life (in englischer Sprache)

Seminar
ECTS: 3

Einzeltermine:
Mi 03.04.24 10:00 - 12:00 Auftakttermin
Mi 10.04.24 10:00 - 12:00 CART 0.01
Mi 08.05.24 10:00 - 12:00 CART 0.01
Mi 29.05.24 10:00 - 12:00 CART 0.01
Mi 26.06.24 10:00 - 12:00 CART 0.01

Auftakttermin am 03.04.2024 von 10-12h in Raum 0.01.
Weitere Termine werden dann abgesprochen.

Jana Schill
03-IMS-SRSESeminar on Topics in Robot Software Engineering (in englischer Sprache)

Seminar
ECTS: 3

Termine:
wöchentlich Di 14:00 - 16:00 MZH 4140 Seminar


Nico Hochgeschwender

General Studies

Informationen zum Thema General Studies findet ihr auch hier: https://www.szi.uni-bremen.de/wp-content/uploads/2021/10/GSListe.pdf

Veranstaltungen aus anderen Studiengängen (Auswahl)

VAKTitel der VeranstaltungDozentIn
04-M30-CEM-SFI-1On Board Data Handling (in englischer Sprache)

Vorlesung
ECTS: 3

Termine:
wöchentlich Do 10:00 - 12:00 IW3 0200
Dr. rer. nat. Frank Dannemann

Graduiertenseminare

VAKTitel der VeranstaltungDozentIn
03-IGRAD-CoSy (03-05-H-711.91)Graduiertenseminar Cognitive Systems (in englischer Sprache)

Seminar

Termine:
zweiwöchentlich (Startwoche: 16) Mi 14:00 - 17:00 Graduiertenseminar
Thomas Dieter Barkowsky

Veranstaltungen für andere Studiengänge

VAKTitel der VeranstaltungDozentIn
META-2024-ALL-IF27. internationale Informatica Feminale (in englischer Sprache)
Informatica Feminale - Summer University for Women in Computing
Sommeruniversität für Frauen in der Informatik /Summer University for Women in Computing

Blockveranstaltung
ECTS: 1-3 (je Kurs/for every course)

60 Lehrveranstaltungen in Deutsch und Englisch für Bachelor- und Masterstudentinnen aller Fächer. Als General Studies sowie teilweise als Fachstudium im Sommersemester 2024 sowie im Wintersemester 2024/25 anerkannt. Alle Einzelangaben, Zeiten und Anmeldungen jederzeit nur über die Website https://www.informatica-feminale.de.
60 courses in German and English for women Bachelor and Master students from all fields of study. Courses are part of General Studies, some are accepted in Informatics; in the summer semester 2024 as well as in winter semester 2024/25. Further information, schedules and registration only on the website https://www.informatica-feminale.de.

Veronika Oechtering
Henrike Illig
META-2024/IF-AG-01Agile Teamwork (in englischer Sprache)
Agile teamwork as the basis of agile project management

Blockveranstaltung
ECTS: 1-3

Einzeltermine:
Fr 24.05.24 16:00 - 18:30 BigBlueButton
Sa 25.05.24 10:00 - 13:00 BigBlueButton
Sa 25.05.24 14:00 - 16:30 BigBlueButton
Fr 31.05.24 16:00 - 18:30 BigBlueButton
Sa 01.06.24 10:00 - 13:00 BigBlueButton
Sa 01.06.24 14:00 - 16:30 BigBlueButton

Agile teamwork is used in many product developments today, initially in software development, but can also be used for any other incrementally buildable product.
It is the particular kind of non-hierarchical cooperation that participants can try out in a small project. We will use it to create a complex product with a storymap.
To get to know agile teamwork Scrum is the most detailed approach.
By applying Scrum roles, you can gain a first insight into agile teamwork.

Course content:
  • Definition of agile teamwork
  • Ambidexterity
  • Scrum roles: Product Owner, Scrum master, Developer
  • Interaction in non-hierarchical teamwork

Meetings:
Friday, 24.05.2024: 4.00 p.m. to 6.30 p.m. (lecture)
Saturday, 25.04.2024: 10.00 am to 1.00 pm and 2.00 pm to 4.30 pm (lecture and teamwork)
Friday, 31.05.2024: 4.00 p.m. to 6.30 p.m. (lecture)
Saturday, 01.06.2024: 10.00 a.m. to 1.00 p.m. and 2.00 p.m. to 4.30 p.m. (lecture and teamwork)

Register via Stud.IP.

Silke Garms
Selma Gebhardt

Sonstige Veranstaltungen ohne Kreditpunkte

VAKTitel der VeranstaltungDozentIn
03-ISONST-EJCEDM Journal Club (in englischer Sprache)

Seminar

Einzeltermine:
Mo 10.02.20 14:00 - 16:00 MZH 5300

Veranstaltung für Doktoranten, jeden 1. Montag im Monat von 14-16h in Raum 5300.

Robert Porzel
Sebastian Höffner
Dr. Nina Wenig
Prof. Dr. Rainer Malaka

Informatica Feminale

Deutschlandweites Sommerstudium fuer Frauen in der Informatik.

Die Informatica Feminale bietet jaehrlich kompakte Lehre zur Informatik fuer Studentinnen aller Hochschularten und fuer an Weiterbildung interessierte Frauen. Studieneinstieg, Verbleib im Studium, Berufsuebergang und lebenslanges Lernen auf universitaerem Niveau stehen dabei gleichermassen im Blickfeld. Dozentinnen und Teilehmerinnen kommen aus dem In- und Ausland. Das Sommerstudium in der Universitaet Bremen ist ein Ort des Experimentierens, um neue Konzepte fuer das Informatikstudium zu finden.

Alle Informationen unter: http://www.informatica-feminale.de/
VAKTitel der VeranstaltungDozentIn
META-2024-ALL-IF27. internationale Informatica Feminale (in englischer Sprache)
Informatica Feminale - Summer University for Women in Computing
Sommeruniversität für Frauen in der Informatik /Summer University for Women in Computing

Blockveranstaltung
ECTS: 1-3 (je Kurs/for every course)

60 Lehrveranstaltungen in Deutsch und Englisch für Bachelor- und Masterstudentinnen aller Fächer. Als General Studies sowie teilweise als Fachstudium im Sommersemester 2024 sowie im Wintersemester 2024/25 anerkannt. Alle Einzelangaben, Zeiten und Anmeldungen jederzeit nur über die Website https://www.informatica-feminale.de.
60 courses in German and English for women Bachelor and Master students from all fields of study. Courses are part of General Studies, some are accepted in Informatics; in the summer semester 2024 as well as in winter semester 2024/25. Further information, schedules and registration only on the website https://www.informatica-feminale.de.

Veronika Oechtering
Henrike Illig

Mathematics, M.Sc.

Area of Specialization: Algebra

Modules: Specialization (A, B, and C with 9 CP each)

The modules Specialization A and Specialization B are compulsory modules (2 x 9 CP = 18 CP). The module Specialization C (9 CP) is a compulsory elective module. This semester you can choose from the following lectures:
VAKTitel der VeranstaltungDozentIn
03-IMAT-APX (03-ME-602.99a)Approximation Algorithms (in englischer Sprache)

Kurs
ECTS: 6

Termine:
wöchentlich Di 10:00 - 12:00 MZH 3150 Kurs
wöchentlich Do 14:00 - 16:00 MZH 1470 MZH 5500 Übung

Profil: SQ, KIKR.
Schwerpunkt: IMA-SQ, IMVT-AI, IMVT-VMC
weitere Studiengänge: M-M-Alg-Num, M-T
https://lvb.informatik.uni-bremen.de/imat/03-imat-apx.pdf

A large number of problems arising in practical scenarios like communication, transportation, planning, logistics etc. can be modeled as combinatorial optimization problems. In most cases, these problems are computationally intractable and one often resorts to heuristics that provide sufficiently good solutions in reasonable amount of runtime. However, in most cases, such heuristics do not provide a worst case guarantee on the performance in comparison to the optimum solution. In this course, we shall study algorithms for combinatorial optimization problems which can provide strong mathematical guarantees on performance. The course aims at developing a toolkit for solving such problems. The lectures will consist of designing polynomial-time algorithms and proving rigorous bounds on their worst case performances.
We review many classical results in the field of approximation algorithms, highlighting different techniques commonly used for the design of such algorithms. Among others, we will treat the following topics:
• Greedy algorithms and Local Search
• Rounding Data and Dynamic Programming
• Deterministic Rounding of Linear Programs (LPs)
• Random Sampling and Randomized Rounding of LPs
• Primal-Dual Methods
• Hardness of Approximation
• Problem Solving under Uncertainty

Dr. Felix Christian Hommelsheim
03-M-SP-15Analytic and Discrete Convex Geometry (in englischer Sprache)

Vorlesung
ECTS: 9

Termine:
wöchentlich Mo 12:00 - 14:00 MZH 4140 Lecture
wöchentlich Mi 10:00 - 12:00 MZH 1100 MZH 5220 (Didaktik-Labor) Lecture
wöchentlich Mi 12:00 - 14:00 MZH 3150 Exercise

Convex Geometry plays an essential role in several branches of Mathematics, from Discrete Mathematics to Harmonic Analysis. We will discuss some major analytic and discrete aspects of convex geometry and some applications. Our topics will range from the boundary structure of convex bodies, particularly polytopes, to Hadwiger's volume characterisation, via geometric and functional inequalities, as well as geometric and analytic symmetrization techniques.

Eugenia Saorin Gomez

Modules: Diversification (A, B, and C with 9 CP each)

The modules Diversification A and Diversification B are compulsory modules (2 x 9 CP = 18 CP). The module Diversification C (9 CP) is a compulsory elective module. This semester you can choose from the following lectures:
VAKTitel der VeranstaltungDozentIn
03-IMAT-APX (03-ME-602.99a)Approximation Algorithms (in englischer Sprache)

Kurs
ECTS: 6

Termine:
wöchentlich Di 10:00 - 12:00 MZH 3150 Kurs
wöchentlich Do 14:00 - 16:00 MZH 1470 MZH 5500 Übung

Profil: SQ, KIKR.
Schwerpunkt: IMA-SQ, IMVT-AI, IMVT-VMC
weitere Studiengänge: M-M-Alg-Num, M-T
https://lvb.informatik.uni-bremen.de/imat/03-imat-apx.pdf

A large number of problems arising in practical scenarios like communication, transportation, planning, logistics etc. can be modeled as combinatorial optimization problems. In most cases, these problems are computationally intractable and one often resorts to heuristics that provide sufficiently good solutions in reasonable amount of runtime. However, in most cases, such heuristics do not provide a worst case guarantee on the performance in comparison to the optimum solution. In this course, we shall study algorithms for combinatorial optimization problems which can provide strong mathematical guarantees on performance. The course aims at developing a toolkit for solving such problems. The lectures will consist of designing polynomial-time algorithms and proving rigorous bounds on their worst case performances.
We review many classical results in the field of approximation algorithms, highlighting different techniques commonly used for the design of such algorithms. Among others, we will treat the following topics:
• Greedy algorithms and Local Search
• Rounding Data and Dynamic Programming
• Deterministic Rounding of Linear Programs (LPs)
• Random Sampling and Randomized Rounding of LPs
• Primal-Dual Methods
• Hardness of Approximation
• Problem Solving under Uncertainty

Dr. Felix Christian Hommelsheim
03-M-SP-12High-Performance-Visualisierung (in englischer Sprache)
High-Performance Visualization
Interaktive Exploration zur Analyse von extrem großen wissenschaftlichen Daten

Vorlesung
ECTS: 4,5 / 6

Termine:
wöchentlich Do 14:00 - 16:00 MZH 1110 Lecture and Exercise

Einzeltermine:
Do 11.07.24 14:00 - 18:00 MZH 1110
Do 22.08.24 - Fr 23.08.24 (Do, Fr) 08:00 - 14:00 MZH 5500

The lecture addresses Interactive Visualization of Huge Scientific Datasets. More information can also be found on the Homepage: https://www.uni-bremen.de/ag-high-performance-visualization

Die Vorlesung beschäftigt sich mit den mathematischen Grundlagen der wissenschaftlichen Visualisierung und behandelt Methoden für das parallele Post-Processing großer wissenschaftlicher Datensätze. Anwendungsbeispiele werden anhand der Open-Source-Software ParaView erläutert.
Homepage zur Veranstaltung: https://www.uni-bremen.de/ag-high-performance-visualization

Prof. Dr. Andreas Gerndt
03-M-SP-14Scientific Programming and Advanced Numerical Methods - an Introduction with Case Studies (in englischer Sprache)

Vorlesung
ECTS: 9

Termine:
wöchentlich Mi 14:00 - 16:00 MZH 2340 Lecture
wöchentlich Do 12:00 - 14:00 MZH 2340 Lecture

Einzeltermine:
Mi 10.07.24 14:00 - 16:00 ZOOM
Mi 17.07.24 14:00 - 16:00 ZOOM
Mo 22.07.24 - Fr 26.07.24 (Mo, Di, Mi, Do, Fr) 10:00 - 16:30

This course provides an introduction to the practice of scientific programming.

Alfred Schmidt
Prof. Dr. Stephan Frickenhaus
03-M-SP-16Mathematical Foundations of Machine Learning (in englischer Sprache)

Vorlesung
ECTS: 9

Termine:
wöchentlich Mo 12:00 - 14:00 MZH 2340 Lecture
wöchentlich Di 12:00 - 14:00 MZH 2340 Lecture
wöchentlich Di 14:00 - 16:00 MZH 2340 Exercise

This course deals with the mathematical foundations of machine learning with a strong focus on classical theory and well-established algorithms like, for example, support vector machines for classification, ridge regression, principal component analysis for dimensionality reduction and k-means clustering. In addition, deep learning with neural networks will be briefly discussed towards the end of the course.

Peter Maaß
Dr. Matthias Beckmann
03-M-SP-20Digital Optimal Control and Optimal Feedback Control (in englischer Sprache)

Vorlesung
ECTS: 9

Termine:
wöchentlich Mo 10:00 - 12:00 Externer Ort: NEOS Gebäude 3. Etage Lecture
wöchentlich Do 10:00 - 12:00 Externer Ort: NEOS Gebäude 3. Etage Lecture
wöchentlich Do 12:00 - 14:00 Externer Ort: NEOS Gebäude 3. Etage Exercise

Die Veranstaltung findet im NEOS Gebäude statt.

Prof. Dr. Christof Büskens
03-M-SP-22Linear and Generalized Linear Regression (Statistics II) (in englischer Sprache)

Vorlesung
ECTS: 9

Termine:
wöchentlich Mi 08:00 - 10:00 MZH 7200 Lecture
wöchentlich Mi 10:00 - 12:00 MZH 7200 Exercise
wöchentlich Do 08:00 - 10:00 MZH 7200 Lecture

Einzeltermine:
Do 25.07.24 10:00 - 12:00 MZH 7200
Maryam Movahedifar
03-M-SP-32Spectral Theory (in englischer Sprache)

Vorlesung
ECTS: 9

Termine:
wöchentlich Mi 14:00 - 16:00 MZH 4140 Lecture
wöchentlich Do 10:00 - 12:00 MZH 4140 Lecture
wöchentlich Do 16:00 - 18:00 MZH 4140 Exercise
PD Dr. Hendrik Vogt
03-M-SP-33Semiparametric Models (in englischer Sprache)

Vorlesung
ECTS: 9

Termine:
wöchentlich Di 09:00 - 10:30 Vorlesung
wöchentlich Mi 14:00 - 16:00 Übung
wöchentlich Fr 12:30 - 14:00 Vorlesung

Die Veranstaltung findet im KKSB statt.

The course will provide an introduction into the theory of semiparametric models. We will introduce and discuss the mathematical statistical theory for such models and will illustrate the utility of semiparametric models with a number of concrete models and data examples. Hence, the lecture and exercises will cover theoretical and practical aspects of semiparametric models. We will use the open statistical software R for the data applications.

Prof. Dr. Werner Brannath
03-M-SP-34Differential Geometry (in englischer Sprache)

Vorlesung
ECTS: 9

Termine:
wöchentlich Di 10:00 - 12:00 MZH 1110 MZH 4140 Lecture
wöchentlich Di 12:00 - 14:00 MZH 1470 Exercise
wöchentlich Mi 16:00 - 18:00 MZH 4140 Lecture

This course will cover manifolds, vector bundles, embeddings and submersions, integral curves and flows, basics of Lie groups, differential forms and integration, Riemannian metrics, geodesics, connections, curvature, and further topics.

Prof. Dr. Anke Dorothea Pohl
03-M-SP-35Selected Topics in Convex Optimization (in englischer Sprache)

Vorlesung
ECTS: 9

Termine:
wöchentlich Mo 10:00 - 12:00 MZH 2340 Lecture
wöchentlich Mi 10:00 - 12:00 MZH 2340 Lecture
wöchentlich Mi 12:00 - 14:00 MZH 2490 (Seminarraum) Exercise

The course will discuss convex optimisation problems and present and analyse algorithms that solve them. Topics will include proximal splitting, acceleration, stochastic algorithms, and performance estimation.

Sebastian Banert
Dirk Lorenz
03-M-SP-36Selected Topics on Optimization for Machine Learning (in englischer Sprache)

Vorlesung
ECTS: 9

Termine:
wöchentlich Do 14:00 - 16:00 MZH 2340 Lecture
wöchentlich Fr 10:00 - 12:00 MZH 2340 Lecture
wöchentlich Fr 12:00 - 14:00 MZH 2340 Exercise
Dirk Lorenz
Lionel Ngoupeyou Tondji

Module: Advanced Communications B (2 x 4,5 CP = 9 CP)

Compulsory module in the area of diversification and in which you must attend a total of two seminars with 4,5 CP each. This semester you can choose from the following seminars:
VAKTitel der VeranstaltungDozentIn
03-M-AC-21Deep Learning for Inverse Problems (in englischer Sprache)

Seminar
ECTS: 4,5/6

Termine:
wöchentlich Mo 14:00 - 16:00 MZH 2340 Seminar
Peter Maaß
03-M-AC-22Advanced Communication Analysis (in englischer Sprache)

Seminar
ECTS: 4,5/6

Termine:
wöchentlich Mi 12:00 - 14:00 MZH 4140 Seminar

Einzeltermine:
Fr 24.05.24 12:00 - 16:00 MZH 1380/1400

In the Seminar Analysis advanced topics in the area of analysis are discussed. The precise topic for Summer semester 2024 will be decided upon with the participants

Prof. Dr. Anke Dorothea Pohl
03-M-AC-23Advanced Robust Control (in englischer Sprache)

Seminar
ECTS: 4,5 / 6

Termine:
wöchentlich Do 10:00 - 12:00 MZH 2340 Seminar
Dr. Chathura Wanigasekara
03-M-AC-28Advanced Numerical Methods for Partial Differential Equations (in englischer Sprache)

Seminar
ECTS: 4,5 / 6

Termine:
wöchentlich Mo 16:00 - 18:00 MZH 2340 Seminar

Seminar on advanced numerical methods for partial differential equations

Alfred Schmidt

Module: Reading Course A (9 CP)

Compulsory module in the area of specialization and with the following course:
VAKTitel der VeranstaltungDozentIn
03-M-RC-ALGReading Course Algebra (in englischer Sprache)

Seminar
ECTS: 9
Prof. Dr. Dmitry Feichtner-Kozlov

Module: Reading Course B (9 CP)

Compulsory module either in the area of specialization or area of diversification and with the following courses:
VAKTitel der VeranstaltungDozentIn
03-M-RC-ALGReading Course Algebra (in englischer Sprache)

Seminar
ECTS: 9
Prof. Dr. Dmitry Feichtner-Kozlov
03-M-RC-ANAReading Course Analysis (in englischer Sprache)

Seminar
ECTS: 9

Einzeltermine:
Do 13.06.24 08:00 - 10:00 MZH 4140

In the Reading Course Analysis advanced topics in the area of analysis are discussed. The precise topic for Summer semester 2024 will be decided upon with the participants.

Prof. Dr. Anke Dorothea Pohl
03-M-RC-NUMReading Course Numerical Analysis (in englischer Sprache)

Seminar
ECTS: 9

Homepage zur Veranstaltung: http://zetem.uni-bremen.de/o2c/veranstaltungen

Analytical and structured thinking, exact formulation of mathematical facts, comprehension of mathematical proofs and learning of proof techniques, independent and creative solving of mathematical problems, knowledge of real analysis, algorithmic approach to solving mathematical problems.

Prof. Dr. Christof Büskens
03-M-RC-STSReading Course Statistics/Stochastics (in englischer Sprache)

Seminar
ECTS: 9

The reading course introduces students to specific topics that may be relevant for the Master's thesis, using mainly original English-language literature (scientific articles and reference books). Students are expected to prepare a seminar talk and an elaboration on the topic.

Prof. Dr. Werner Brannath
Prof. Dr. Thorsten-Ingo Dickhaus

Area of Specialization: Analysis

Modules: Specialization (A, B, and C with 9 CP each)

The modules Specialization A and Specialization B are compulsory modules (2 x 9 CP = 18 CP). The module Specialization C (9 CP) is a compulsory elective module. This semester you can choose from the following lectures:
VAKTitel der VeranstaltungDozentIn
03-M-SP-16Mathematical Foundations of Machine Learning (in englischer Sprache)

Vorlesung
ECTS: 9

Termine:
wöchentlich Mo 12:00 - 14:00 MZH 2340 Lecture
wöchentlich Di 12:00 - 14:00 MZH 2340 Lecture
wöchentlich Di 14:00 - 16:00 MZH 2340 Exercise

This course deals with the mathematical foundations of machine learning with a strong focus on classical theory and well-established algorithms like, for example, support vector machines for classification, ridge regression, principal component analysis for dimensionality reduction and k-means clustering. In addition, deep learning with neural networks will be briefly discussed towards the end of the course.

Peter Maaß
Dr. Matthias Beckmann
03-M-SP-32Spectral Theory (in englischer Sprache)

Vorlesung
ECTS: 9

Termine:
wöchentlich Mi 14:00 - 16:00 MZH 4140 Lecture
wöchentlich Do 10:00 - 12:00 MZH 4140 Lecture
wöchentlich Do 16:00 - 18:00 MZH 4140 Exercise
PD Dr. Hendrik Vogt
03-M-SP-34Differential Geometry (in englischer Sprache)

Vorlesung
ECTS: 9

Termine:
wöchentlich Di 10:00 - 12:00 MZH 1110 MZH 4140 Lecture
wöchentlich Di 12:00 - 14:00 MZH 1470 Exercise
wöchentlich Mi 16:00 - 18:00 MZH 4140 Lecture

This course will cover manifolds, vector bundles, embeddings and submersions, integral curves and flows, basics of Lie groups, differential forms and integration, Riemannian metrics, geodesics, connections, curvature, and further topics.

Prof. Dr. Anke Dorothea Pohl

Modules: Diversification (A, B, and C with 9 CP each)

The modules Diversification A and Diversification B are compulsory modules (2 x 9 CP = 18 CP). The module Diversification C (9 CP) is a compulsory elective module. This semester you can choose from the following lectures:
VAKTitel der VeranstaltungDozentIn
03-IMAT-APX (03-ME-602.99a)Approximation Algorithms (in englischer Sprache)

Kurs
ECTS: 6

Termine:
wöchentlich Di 10:00 - 12:00 MZH 3150 Kurs
wöchentlich Do 14:00 - 16:00 MZH 1470 MZH 5500 Übung

Profil: SQ, KIKR.
Schwerpunkt: IMA-SQ, IMVT-AI, IMVT-VMC
weitere Studiengänge: M-M-Alg-Num, M-T
https://lvb.informatik.uni-bremen.de/imat/03-imat-apx.pdf

A large number of problems arising in practical scenarios like communication, transportation, planning, logistics etc. can be modeled as combinatorial optimization problems. In most cases, these problems are computationally intractable and one often resorts to heuristics that provide sufficiently good solutions in reasonable amount of runtime. However, in most cases, such heuristics do not provide a worst case guarantee on the performance in comparison to the optimum solution. In this course, we shall study algorithms for combinatorial optimization problems which can provide strong mathematical guarantees on performance. The course aims at developing a toolkit for solving such problems. The lectures will consist of designing polynomial-time algorithms and proving rigorous bounds on their worst case performances.
We review many classical results in the field of approximation algorithms, highlighting different techniques commonly used for the design of such algorithms. Among others, we will treat the following topics:
• Greedy algorithms and Local Search
• Rounding Data and Dynamic Programming
• Deterministic Rounding of Linear Programs (LPs)
• Random Sampling and Randomized Rounding of LPs
• Primal-Dual Methods
• Hardness of Approximation
• Problem Solving under Uncertainty

Dr. Felix Christian Hommelsheim
03-M-SP-12High-Performance-Visualisierung (in englischer Sprache)
High-Performance Visualization
Interaktive Exploration zur Analyse von extrem großen wissenschaftlichen Daten

Vorlesung
ECTS: 4,5 / 6

Termine:
wöchentlich Do 14:00 - 16:00 MZH 1110 Lecture and Exercise

Einzeltermine:
Do 11.07.24 14:00 - 18:00 MZH 1110
Do 22.08.24 - Fr 23.08.24 (Do, Fr) 08:00 - 14:00 MZH 5500

The lecture addresses Interactive Visualization of Huge Scientific Datasets. More information can also be found on the Homepage: https://www.uni-bremen.de/ag-high-performance-visualization

Die Vorlesung beschäftigt sich mit den mathematischen Grundlagen der wissenschaftlichen Visualisierung und behandelt Methoden für das parallele Post-Processing großer wissenschaftlicher Datensätze. Anwendungsbeispiele werden anhand der Open-Source-Software ParaView erläutert.
Homepage zur Veranstaltung: https://www.uni-bremen.de/ag-high-performance-visualization

Prof. Dr. Andreas Gerndt
03-M-SP-14Scientific Programming and Advanced Numerical Methods - an Introduction with Case Studies (in englischer Sprache)

Vorlesung
ECTS: 9

Termine:
wöchentlich Mi 14:00 - 16:00 MZH 2340 Lecture
wöchentlich Do 12:00 - 14:00 MZH 2340 Lecture

Einzeltermine:
Mi 10.07.24 14:00 - 16:00 ZOOM
Mi 17.07.24 14:00 - 16:00 ZOOM
Mo 22.07.24 - Fr 26.07.24 (Mo, Di, Mi, Do, Fr) 10:00 - 16:30

This course provides an introduction to the practice of scientific programming.

Alfred Schmidt
Prof. Dr. Stephan Frickenhaus
03-M-SP-15Analytic and Discrete Convex Geometry (in englischer Sprache)

Vorlesung
ECTS: 9

Termine:
wöchentlich Mo 12:00 - 14:00 MZH 4140 Lecture
wöchentlich Mi 10:00 - 12:00 MZH 1100 MZH 5220 (Didaktik-Labor) Lecture
wöchentlich Mi 12:00 - 14:00 MZH 3150 Exercise

Convex Geometry plays an essential role in several branches of Mathematics, from Discrete Mathematics to Harmonic Analysis. We will discuss some major analytic and discrete aspects of convex geometry and some applications. Our topics will range from the boundary structure of convex bodies, particularly polytopes, to Hadwiger's volume characterisation, via geometric and functional inequalities, as well as geometric and analytic symmetrization techniques.

Eugenia Saorin Gomez
03-M-SP-16Mathematical Foundations of Machine Learning (in englischer Sprache)

Vorlesung
ECTS: 9

Termine:
wöchentlich Mo 12:00 - 14:00 MZH 2340 Lecture
wöchentlich Di 12:00 - 14:00 MZH 2340 Lecture
wöchentlich Di 14:00 - 16:00 MZH 2340 Exercise

This course deals with the mathematical foundations of machine learning with a strong focus on classical theory and well-established algorithms like, for example, support vector machines for classification, ridge regression, principal component analysis for dimensionality reduction and k-means clustering. In addition, deep learning with neural networks will be briefly discussed towards the end of the course.

Peter Maaß
Dr. Matthias Beckmann
03-M-SP-20Digital Optimal Control and Optimal Feedback Control (in englischer Sprache)

Vorlesung
ECTS: 9

Termine:
wöchentlich Mo 10:00 - 12:00 Externer Ort: NEOS Gebäude 3. Etage Lecture
wöchentlich Do 10:00 - 12:00 Externer Ort: NEOS Gebäude 3. Etage Lecture
wöchentlich Do 12:00 - 14:00 Externer Ort: NEOS Gebäude 3. Etage Exercise

Die Veranstaltung findet im NEOS Gebäude statt.

Prof. Dr. Christof Büskens
03-M-SP-22Linear and Generalized Linear Regression (Statistics II) (in englischer Sprache)

Vorlesung
ECTS: 9

Termine:
wöchentlich Mi 08:00 - 10:00 MZH 7200 Lecture
wöchentlich Mi 10:00 - 12:00 MZH 7200 Exercise
wöchentlich Do 08:00 - 10:00 MZH 7200 Lecture

Einzeltermine:
Do 25.07.24 10:00 - 12:00 MZH 7200
Maryam Movahedifar
03-M-SP-33Semiparametric Models (in englischer Sprache)

Vorlesung
ECTS: 9

Termine:
wöchentlich Di 09:00 - 10:30 Vorlesung
wöchentlich Mi 14:00 - 16:00 Übung
wöchentlich Fr 12:30 - 14:00 Vorlesung

Die Veranstaltung findet im KKSB statt.

The course will provide an introduction into the theory of semiparametric models. We will introduce and discuss the mathematical statistical theory for such models and will illustrate the utility of semiparametric models with a number of concrete models and data examples. Hence, the lecture and exercises will cover theoretical and practical aspects of semiparametric models. We will use the open statistical software R for the data applications.

Prof. Dr. Werner Brannath
03-M-SP-35Selected Topics in Convex Optimization (in englischer Sprache)

Vorlesung
ECTS: 9

Termine:
wöchentlich Mo 10:00 - 12:00 MZH 2340 Lecture
wöchentlich Mi 10:00 - 12:00 MZH 2340 Lecture
wöchentlich Mi 12:00 - 14:00 MZH 2490 (Seminarraum) Exercise

The course will discuss convex optimisation problems and present and analyse algorithms that solve them. Topics will include proximal splitting, acceleration, stochastic algorithms, and performance estimation.

Sebastian Banert
Dirk Lorenz
03-M-SP-36Selected Topics on Optimization for Machine Learning (in englischer Sprache)

Vorlesung
ECTS: 9

Termine:
wöchentlich Do 14:00 - 16:00 MZH 2340 Lecture
wöchentlich Fr 10:00 - 12:00 MZH 2340 Lecture
wöchentlich Fr 12:00 - 14:00 MZH 2340 Exercise
Dirk Lorenz
Lionel Ngoupeyou Tondji

Module: Advanced Communications A (2 x 4,5 CP = 9 CP)

Compulsory module in the area of specialization and in which you must attend a total of two seminars with 4,5 CP each. This semester you can choose from the following seminars:
VAKTitel der VeranstaltungDozentIn
03-M-AC-22Advanced Communication Analysis (in englischer Sprache)

Seminar
ECTS: 4,5/6

Termine:
wöchentlich Mi 12:00 - 14:00 MZH 4140 Seminar

Einzeltermine:
Fr 24.05.24 12:00 - 16:00 MZH 1380/1400

In the Seminar Analysis advanced topics in the area of analysis are discussed. The precise topic for Summer semester 2024 will be decided upon with the participants

Prof. Dr. Anke Dorothea Pohl

Module: Advanced Communications B (2 x 4,5 CP = 9 CP)

Compulsory module in the area of diversification and in which you must attend a total of two seminars with 4,5 CP each. This semester you can choose from the following seminars:
VAKTitel der VeranstaltungDozentIn
03-M-AC-21Deep Learning for Inverse Problems (in englischer Sprache)

Seminar
ECTS: 4,5/6

Termine:
wöchentlich Mo 14:00 - 16:00 MZH 2340 Seminar
Peter Maaß
03-M-AC-23Advanced Robust Control (in englischer Sprache)

Seminar
ECTS: 4,5 / 6

Termine:
wöchentlich Do 10:00 - 12:00 MZH 2340 Seminar
Dr. Chathura Wanigasekara
03-M-AC-28Advanced Numerical Methods for Partial Differential Equations (in englischer Sprache)

Seminar
ECTS: 4,5 / 6

Termine:
wöchentlich Mo 16:00 - 18:00 MZH 2340 Seminar

Seminar on advanced numerical methods for partial differential equations

Alfred Schmidt

Module: Reading Course A (9 CP)

Compulsory module in the area of specialization and with the following course:
VAKTitel der VeranstaltungDozentIn
03-M-RC-ANAReading Course Analysis (in englischer Sprache)

Seminar
ECTS: 9

Einzeltermine:
Do 13.06.24 08:00 - 10:00 MZH 4140

In the Reading Course Analysis advanced topics in the area of analysis are discussed. The precise topic for Summer semester 2024 will be decided upon with the participants.

Prof. Dr. Anke Dorothea Pohl

Module: Reading Course B (9 CP)

Compulsory module either in the area of specialization or area of diversification and with the following courses:
VAKTitel der VeranstaltungDozentIn
03-M-RC-ALGReading Course Algebra (in englischer Sprache)

Seminar
ECTS: 9
Prof. Dr. Dmitry Feichtner-Kozlov
03-M-RC-ANAReading Course Analysis (in englischer Sprache)

Seminar
ECTS: 9

Einzeltermine:
Do 13.06.24 08:00 - 10:00 MZH 4140

In the Reading Course Analysis advanced topics in the area of analysis are discussed. The precise topic for Summer semester 2024 will be decided upon with the participants.

Prof. Dr. Anke Dorothea Pohl
03-M-RC-NUMReading Course Numerical Analysis (in englischer Sprache)

Seminar
ECTS: 9

Homepage zur Veranstaltung: http://zetem.uni-bremen.de/o2c/veranstaltungen

Analytical and structured thinking, exact formulation of mathematical facts, comprehension of mathematical proofs and learning of proof techniques, independent and creative solving of mathematical problems, knowledge of real analysis, algorithmic approach to solving mathematical problems.

Prof. Dr. Christof Büskens
03-M-RC-STSReading Course Statistics/Stochastics (in englischer Sprache)

Seminar
ECTS: 9

The reading course introduces students to specific topics that may be relevant for the Master's thesis, using mainly original English-language literature (scientific articles and reference books). Students are expected to prepare a seminar talk and an elaboration on the topic.

Prof. Dr. Werner Brannath
Prof. Dr. Thorsten-Ingo Dickhaus

Area of Specialization: Numerical Analysis

Modules: Specialization (A, B, and C with 9 CP each)

The modules Specialization A and Specialization B are compulsory modules (2 x 9 CP = 18 CP). The module Specialization C (9 CP) is a compulsory elective module. This semester you can choose from the following lectures:
VAKTitel der VeranstaltungDozentIn
03-IMAT-APX (03-ME-602.99a)Approximation Algorithms (in englischer Sprache)

Kurs
ECTS: 6

Termine:
wöchentlich Di 10:00 - 12:00 MZH 3150 Kurs
wöchentlich Do 14:00 - 16:00 MZH 1470 MZH 5500 Übung

Profil: SQ, KIKR.
Schwerpunkt: IMA-SQ, IMVT-AI, IMVT-VMC
weitere Studiengänge: M-M-Alg-Num, M-T
https://lvb.informatik.uni-bremen.de/imat/03-imat-apx.pdf

A large number of problems arising in practical scenarios like communication, transportation, planning, logistics etc. can be modeled as combinatorial optimization problems. In most cases, these problems are computationally intractable and one often resorts to heuristics that provide sufficiently good solutions in reasonable amount of runtime. However, in most cases, such heuristics do not provide a worst case guarantee on the performance in comparison to the optimum solution. In this course, we shall study algorithms for combinatorial optimization problems which can provide strong mathematical guarantees on performance. The course aims at developing a toolkit for solving such problems. The lectures will consist of designing polynomial-time algorithms and proving rigorous bounds on their worst case performances.
We review many classical results in the field of approximation algorithms, highlighting different techniques commonly used for the design of such algorithms. Among others, we will treat the following topics:
• Greedy algorithms and Local Search
• Rounding Data and Dynamic Programming
• Deterministic Rounding of Linear Programs (LPs)
• Random Sampling and Randomized Rounding of LPs
• Primal-Dual Methods
• Hardness of Approximation
• Problem Solving under Uncertainty

Dr. Felix Christian Hommelsheim
03-M-SP-12High-Performance-Visualisierung (in englischer Sprache)
High-Performance Visualization
Interaktive Exploration zur Analyse von extrem großen wissenschaftlichen Daten

Vorlesung
ECTS: 4,5 / 6

Termine:
wöchentlich Do 14:00 - 16:00 MZH 1110 Lecture and Exercise

Einzeltermine:
Do 11.07.24 14:00 - 18:00 MZH 1110
Do 22.08.24 - Fr 23.08.24 (Do, Fr) 08:00 - 14:00 MZH 5500

The lecture addresses Interactive Visualization of Huge Scientific Datasets. More information can also be found on the Homepage: https://www.uni-bremen.de/ag-high-performance-visualization

Die Vorlesung beschäftigt sich mit den mathematischen Grundlagen der wissenschaftlichen Visualisierung und behandelt Methoden für das parallele Post-Processing großer wissenschaftlicher Datensätze. Anwendungsbeispiele werden anhand der Open-Source-Software ParaView erläutert.
Homepage zur Veranstaltung: https://www.uni-bremen.de/ag-high-performance-visualization

Prof. Dr. Andreas Gerndt
03-M-SP-14Scientific Programming and Advanced Numerical Methods - an Introduction with Case Studies (in englischer Sprache)

Vorlesung
ECTS: 9

Termine:
wöchentlich Mi 14:00 - 16:00 MZH 2340 Lecture
wöchentlich Do 12:00 - 14:00 MZH 2340 Lecture

Einzeltermine:
Mi 10.07.24 14:00 - 16:00 ZOOM
Mi 17.07.24 14:00 - 16:00 ZOOM
Mo 22.07.24 - Fr 26.07.24 (Mo, Di, Mi, Do, Fr) 10:00 - 16:30

This course provides an introduction to the practice of scientific programming.

Alfred Schmidt
Prof. Dr. Stephan Frickenhaus
03-M-SP-16Mathematical Foundations of Machine Learning (in englischer Sprache)

Vorlesung
ECTS: 9

Termine:
wöchentlich Mo 12:00 - 14:00 MZH 2340 Lecture
wöchentlich Di 12:00 - 14:00 MZH 2340 Lecture
wöchentlich Di 14:00 - 16:00 MZH 2340 Exercise

This course deals with the mathematical foundations of machine learning with a strong focus on classical theory and well-established algorithms like, for example, support vector machines for classification, ridge regression, principal component analysis for dimensionality reduction and k-means clustering. In addition, deep learning with neural networks will be briefly discussed towards the end of the course.

Peter Maaß
Dr. Matthias Beckmann
03-M-SP-20Digital Optimal Control and Optimal Feedback Control (in englischer Sprache)

Vorlesung
ECTS: 9

Termine:
wöchentlich Mo 10:00 - 12:00 Externer Ort: NEOS Gebäude 3. Etage Lecture
wöchentlich Do 10:00 - 12:00 Externer Ort: NEOS Gebäude 3. Etage Lecture
wöchentlich Do 12:00 - 14:00 Externer Ort: NEOS Gebäude 3. Etage Exercise

Die Veranstaltung findet im NEOS Gebäude statt.

Prof. Dr. Christof Büskens
03-M-SP-35Selected Topics in Convex Optimization (in englischer Sprache)

Vorlesung
ECTS: 9

Termine:
wöchentlich Mo 10:00 - 12:00 MZH 2340 Lecture
wöchentlich Mi 10:00 - 12:00 MZH 2340 Lecture
wöchentlich Mi 12:00 - 14:00 MZH 2490 (Seminarraum) Exercise

The course will discuss convex optimisation problems and present and analyse algorithms that solve them. Topics will include proximal splitting, acceleration, stochastic algorithms, and performance estimation.

Sebastian Banert
Dirk Lorenz
03-M-SP-36Selected Topics on Optimization for Machine Learning (in englischer Sprache)

Vorlesung
ECTS: 9

Termine:
wöchentlich Do 14:00 - 16:00 MZH 2340 Lecture
wöchentlich Fr 10:00 - 12:00 MZH 2340 Lecture
wöchentlich Fr 12:00 - 14:00 MZH 2340 Exercise
Dirk Lorenz
Lionel Ngoupeyou Tondji

Modules: Diversification (A, B, and C with 9 CP each)

The modules Diversification A and Diversification B are compulsory modules (2 x 9 CP = 18 CP). The module Diversification C (9 CP) is a compulsory elective module. This semester you can choose from the following lectures:
VAKTitel der VeranstaltungDozentIn
03-IMAT-APX (03-ME-602.99a)Approximation Algorithms (in englischer Sprache)

Kurs
ECTS: 6

Termine:
wöchentlich Di 10:00 - 12:00 MZH 3150 Kurs
wöchentlich Do 14:00 - 16:00 MZH 1470 MZH 5500 Übung

Profil: SQ, KIKR.
Schwerpunkt: IMA-SQ, IMVT-AI, IMVT-VMC
weitere Studiengänge: M-M-Alg-Num, M-T
https://lvb.informatik.uni-bremen.de/imat/03-imat-apx.pdf

A large number of problems arising in practical scenarios like communication, transportation, planning, logistics etc. can be modeled as combinatorial optimization problems. In most cases, these problems are computationally intractable and one often resorts to heuristics that provide sufficiently good solutions in reasonable amount of runtime. However, in most cases, such heuristics do not provide a worst case guarantee on the performance in comparison to the optimum solution. In this course, we shall study algorithms for combinatorial optimization problems which can provide strong mathematical guarantees on performance. The course aims at developing a toolkit for solving such problems. The lectures will consist of designing polynomial-time algorithms and proving rigorous bounds on their worst case performances.
We review many classical results in the field of approximation algorithms, highlighting different techniques commonly used for the design of such algorithms. Among others, we will treat the following topics:
• Greedy algorithms and Local Search
• Rounding Data and Dynamic Programming
• Deterministic Rounding of Linear Programs (LPs)
• Random Sampling and Randomized Rounding of LPs
• Primal-Dual Methods
• Hardness of Approximation
• Problem Solving under Uncertainty

Dr. Felix Christian Hommelsheim
03-M-SP-15Analytic and Discrete Convex Geometry (in englischer Sprache)

Vorlesung
ECTS: 9

Termine:
wöchentlich Mo 12:00 - 14:00 MZH 4140 Lecture
wöchentlich Mi 10:00 - 12:00 MZH 1100 MZH 5220 (Didaktik-Labor) Lecture
wöchentlich Mi 12:00 - 14:00 MZH 3150 Exercise

Convex Geometry plays an essential role in several branches of Mathematics, from Discrete Mathematics to Harmonic Analysis. We will discuss some major analytic and discrete aspects of convex geometry and some applications. Our topics will range from the boundary structure of convex bodies, particularly polytopes, to Hadwiger's volume characterisation, via geometric and functional inequalities, as well as geometric and analytic symmetrization techniques.

Eugenia Saorin Gomez
03-M-SP-16Mathematical Foundations of Machine Learning (in englischer Sprache)

Vorlesung
ECTS: 9

Termine:
wöchentlich Mo 12:00 - 14:00 MZH 2340 Lecture
wöchentlich Di 12:00 - 14:00 MZH 2340 Lecture
wöchentlich Di 14:00 - 16:00 MZH 2340 Exercise

This course deals with the mathematical foundations of machine learning with a strong focus on classical theory and well-established algorithms like, for example, support vector machines for classification, ridge regression, principal component analysis for dimensionality reduction and k-means clustering. In addition, deep learning with neural networks will be briefly discussed towards the end of the course.

Peter Maaß
Dr. Matthias Beckmann
03-M-SP-22Linear and Generalized Linear Regression (Statistics II) (in englischer Sprache)

Vorlesung
ECTS: 9

Termine:
wöchentlich Mi 08:00 - 10:00 MZH 7200 Lecture
wöchentlich Mi 10:00 - 12:00 MZH 7200 Exercise
wöchentlich Do 08:00 - 10:00 MZH 7200 Lecture

Einzeltermine:
Do 25.07.24 10:00 - 12:00 MZH 7200
Maryam Movahedifar
03-M-SP-32Spectral Theory (in englischer Sprache)

Vorlesung
ECTS: 9

Termine:
wöchentlich Mi 14:00 - 16:00 MZH 4140 Lecture
wöchentlich Do 10:00 - 12:00 MZH 4140 Lecture
wöchentlich Do 16:00 - 18:00 MZH 4140 Exercise
PD Dr. Hendrik Vogt
03-M-SP-33Semiparametric Models (in englischer Sprache)

Vorlesung
ECTS: 9

Termine:
wöchentlich Di 09:00 - 10:30 Vorlesung
wöchentlich Mi 14:00 - 16:00 Übung
wöchentlich Fr 12:30 - 14:00 Vorlesung

Die Veranstaltung findet im KKSB statt.

The course will provide an introduction into the theory of semiparametric models. We will introduce and discuss the mathematical statistical theory for such models and will illustrate the utility of semiparametric models with a number of concrete models and data examples. Hence, the lecture and exercises will cover theoretical and practical aspects of semiparametric models. We will use the open statistical software R for the data applications.

Prof. Dr. Werner Brannath
03-M-SP-34Differential Geometry (in englischer Sprache)

Vorlesung
ECTS: 9

Termine:
wöchentlich Di 10:00 - 12:00 MZH 1110 MZH 4140 Lecture
wöchentlich Di 12:00 - 14:00 MZH 1470 Exercise
wöchentlich Mi 16:00 - 18:00 MZH 4140 Lecture

This course will cover manifolds, vector bundles, embeddings and submersions, integral curves and flows, basics of Lie groups, differential forms and integration, Riemannian metrics, geodesics, connections, curvature, and further topics.

Prof. Dr. Anke Dorothea Pohl

Module: Advanced Communications A (2 x 4,5 CP = 9 CP)

Compulsory module in the area of specialization and in which you must attend a total of two seminars with 4,5 CP each. This semester you can choose from the following seminars:
VAKTitel der VeranstaltungDozentIn
03-M-AC-21Deep Learning for Inverse Problems (in englischer Sprache)

Seminar
ECTS: 4,5/6

Termine:
wöchentlich Mo 14:00 - 16:00 MZH 2340 Seminar
Peter Maaß
03-M-AC-23Advanced Robust Control (in englischer Sprache)

Seminar
ECTS: 4,5 / 6

Termine:
wöchentlich Do 10:00 - 12:00 MZH 2340 Seminar
Dr. Chathura Wanigasekara
03-M-AC-28Advanced Numerical Methods for Partial Differential Equations (in englischer Sprache)

Seminar
ECTS: 4,5 / 6

Termine:
wöchentlich Mo 16:00 - 18:00 MZH 2340 Seminar

Seminar on advanced numerical methods for partial differential equations

Alfred Schmidt

Module: Advanced Communications B (2 x 4,5 CP = 9 CP)

Compulsory module in the area of diversification and in which you must attend a total of two seminars with 4,5 CP each. This semester you can choose from the following seminars:
VAKTitel der VeranstaltungDozentIn
03-M-AC-22Advanced Communication Analysis (in englischer Sprache)

Seminar
ECTS: 4,5/6

Termine:
wöchentlich Mi 12:00 - 14:00 MZH 4140 Seminar

Einzeltermine:
Fr 24.05.24 12:00 - 16:00 MZH 1380/1400

In the Seminar Analysis advanced topics in the area of analysis are discussed. The precise topic for Summer semester 2024 will be decided upon with the participants

Prof. Dr. Anke Dorothea Pohl

Module: Reading Course A (9 CP)

Compulsory module in the area of specialization and with the following course:
VAKTitel der VeranstaltungDozentIn
03-M-RC-NUMReading Course Numerical Analysis (in englischer Sprache)

Seminar
ECTS: 9

Homepage zur Veranstaltung: http://zetem.uni-bremen.de/o2c/veranstaltungen

Analytical and structured thinking, exact formulation of mathematical facts, comprehension of mathematical proofs and learning of proof techniques, independent and creative solving of mathematical problems, knowledge of real analysis, algorithmic approach to solving mathematical problems.

Prof. Dr. Christof Büskens

Module: Reading Course B (9 CP)

Compulsory module either in the area of specialization or area of diversification and with the following courses:
VAKTitel der VeranstaltungDozentIn
03-M-RC-ALGReading Course Algebra (in englischer Sprache)

Seminar
ECTS: 9
Prof. Dr. Dmitry Feichtner-Kozlov
03-M-RC-ANAReading Course Analysis (in englischer Sprache)

Seminar
ECTS: 9

Einzeltermine:
Do 13.06.24 08:00 - 10:00 MZH 4140

In the Reading Course Analysis advanced topics in the area of analysis are discussed. The precise topic for Summer semester 2024 will be decided upon with the participants.

Prof. Dr. Anke Dorothea Pohl
03-M-RC-NUMReading Course Numerical Analysis (in englischer Sprache)

Seminar
ECTS: 9

Homepage zur Veranstaltung: http://zetem.uni-bremen.de/o2c/veranstaltungen

Analytical and structured thinking, exact formulation of mathematical facts, comprehension of mathematical proofs and learning of proof techniques, independent and creative solving of mathematical problems, knowledge of real analysis, algorithmic approach to solving mathematical problems.

Prof. Dr. Christof Büskens
03-M-RC-STSReading Course Statistics/Stochastics (in englischer Sprache)

Seminar
ECTS: 9

The reading course introduces students to specific topics that may be relevant for the Master's thesis, using mainly original English-language literature (scientific articles and reference books). Students are expected to prepare a seminar talk and an elaboration on the topic.

Prof. Dr. Werner Brannath
Prof. Dr. Thorsten-Ingo Dickhaus

Area of Specialization: Statistics/Stochastics

Modules: Specialization (A, B, and C with 9 CP each)

The modules Specialization A and Specialization B are compulsory modules (2 x 9 CP = 18 CP). The module Specialization C (9 CP) is a compulsory elective module. This semester you can choose from the following lectures:
VAKTitel der VeranstaltungDozentIn
03-M-SP-22Linear and Generalized Linear Regression (Statistics II) (in englischer Sprache)

Vorlesung
ECTS: 9

Termine:
wöchentlich Mi 08:00 - 10:00 MZH 7200 Lecture
wöchentlich Mi 10:00 - 12:00 MZH 7200 Exercise
wöchentlich Do 08:00 - 10:00 MZH 7200 Lecture

Einzeltermine:
Do 25.07.24 10:00 - 12:00 MZH 7200
Maryam Movahedifar
03-M-SP-33Semiparametric Models (in englischer Sprache)

Vorlesung
ECTS: 9

Termine:
wöchentlich Di 09:00 - 10:30 Vorlesung
wöchentlich Mi 14:00 - 16:00 Übung
wöchentlich Fr 12:30 - 14:00 Vorlesung

Die Veranstaltung findet im KKSB statt.

The course will provide an introduction into the theory of semiparametric models. We will introduce and discuss the mathematical statistical theory for such models and will illustrate the utility of semiparametric models with a number of concrete models and data examples. Hence, the lecture and exercises will cover theoretical and practical aspects of semiparametric models. We will use the open statistical software R for the data applications.

Prof. Dr. Werner Brannath

Modules: Diversification (A, B, and C with 9 CP each)

The modules Diversification A and Diversification B are compulsory modules (2 x 9 CP = 18 CP). The module Diversification C (9 CP) is a compulsory elective module. This semester you can choose from the following lectures:
VAKTitel der VeranstaltungDozentIn
03-IMAT-APX (03-ME-602.99a)Approximation Algorithms (in englischer Sprache)

Kurs
ECTS: 6

Termine:
wöchentlich Di 10:00 - 12:00 MZH 3150 Kurs
wöchentlich Do 14:00 - 16:00 MZH 1470 MZH 5500 Übung

Profil: SQ, KIKR.
Schwerpunkt: IMA-SQ, IMVT-AI, IMVT-VMC
weitere Studiengänge: M-M-Alg-Num, M-T
https://lvb.informatik.uni-bremen.de/imat/03-imat-apx.pdf

A large number of problems arising in practical scenarios like communication, transportation, planning, logistics etc. can be modeled as combinatorial optimization problems. In most cases, these problems are computationally intractable and one often resorts to heuristics that provide sufficiently good solutions in reasonable amount of runtime. However, in most cases, such heuristics do not provide a worst case guarantee on the performance in comparison to the optimum solution. In this course, we shall study algorithms for combinatorial optimization problems which can provide strong mathematical guarantees on performance. The course aims at developing a toolkit for solving such problems. The lectures will consist of designing polynomial-time algorithms and proving rigorous bounds on their worst case performances.
We review many classical results in the field of approximation algorithms, highlighting different techniques commonly used for the design of such algorithms. Among others, we will treat the following topics:
• Greedy algorithms and Local Search
• Rounding Data and Dynamic Programming
• Deterministic Rounding of Linear Programs (LPs)
• Random Sampling and Randomized Rounding of LPs
• Primal-Dual Methods
• Hardness of Approximation
• Problem Solving under Uncertainty

Dr. Felix Christian Hommelsheim
03-M-SP-12High-Performance-Visualisierung (in englischer Sprache)
High-Performance Visualization
Interaktive Exploration zur Analyse von extrem großen wissenschaftlichen Daten

Vorlesung
ECTS: 4,5 / 6

Termine:
wöchentlich Do 14:00 - 16:00 MZH 1110 Lecture and Exercise

Einzeltermine:
Do 11.07.24 14:00 - 18:00 MZH 1110
Do 22.08.24 - Fr 23.08.24 (Do, Fr) 08:00 - 14:00 MZH 5500

The lecture addresses Interactive Visualization of Huge Scientific Datasets. More information can also be found on the Homepage: https://www.uni-bremen.de/ag-high-performance-visualization

Die Vorlesung beschäftigt sich mit den mathematischen Grundlagen der wissenschaftlichen Visualisierung und behandelt Methoden für das parallele Post-Processing großer wissenschaftlicher Datensätze. Anwendungsbeispiele werden anhand der Open-Source-Software ParaView erläutert.
Homepage zur Veranstaltung: https://www.uni-bremen.de/ag-high-performance-visualization

Prof. Dr. Andreas Gerndt
03-M-SP-14Scientific Programming and Advanced Numerical Methods - an Introduction with Case Studies (in englischer Sprache)

Vorlesung
ECTS: 9

Termine:
wöchentlich Mi 14:00 - 16:00 MZH 2340 Lecture
wöchentlich Do 12:00 - 14:00 MZH 2340 Lecture

Einzeltermine:
Mi 10.07.24 14:00 - 16:00 ZOOM
Mi 17.07.24 14:00 - 16:00 ZOOM
Mo 22.07.24 - Fr 26.07.24 (Mo, Di, Mi, Do, Fr) 10:00 - 16:30

This course provides an introduction to the practice of scientific programming.

Alfred Schmidt
Prof. Dr. Stephan Frickenhaus
03-M-SP-15Analytic and Discrete Convex Geometry (in englischer Sprache)

Vorlesung
ECTS: 9

Termine:
wöchentlich Mo 12:00 - 14:00 MZH 4140 Lecture
wöchentlich Mi 10:00 - 12:00 MZH 1100 MZH 5220 (Didaktik-Labor) Lecture
wöchentlich Mi 12:00 - 14:00 MZH 3150 Exercise

Convex Geometry plays an essential role in several branches of Mathematics, from Discrete Mathematics to Harmonic Analysis. We will discuss some major analytic and discrete aspects of convex geometry and some applications. Our topics will range from the boundary structure of convex bodies, particularly polytopes, to Hadwiger's volume characterisation, via geometric and functional inequalities, as well as geometric and analytic symmetrization techniques.

Eugenia Saorin Gomez
03-M-SP-16Mathematical Foundations of Machine Learning (in englischer Sprache)

Vorlesung
ECTS: 9

Termine:
wöchentlich Mo 12:00 - 14:00 MZH 2340 Lecture
wöchentlich Di 12:00 - 14:00 MZH 2340 Lecture
wöchentlich Di 14:00 - 16:00 MZH 2340 Exercise

This course deals with the mathematical foundations of machine learning with a strong focus on classical theory and well-established algorithms like, for example, support vector machines for classification, ridge regression, principal component analysis for dimensionality reduction and k-means clustering. In addition, deep learning with neural networks will be briefly discussed towards the end of the course.

Peter Maaß
Dr. Matthias Beckmann
03-M-SP-20Digital Optimal Control and Optimal Feedback Control (in englischer Sprache)

Vorlesung
ECTS: 9

Termine:
wöchentlich Mo 10:00 - 12:00 Externer Ort: NEOS Gebäude 3. Etage Lecture
wöchentlich Do 10:00 - 12:00 Externer Ort: NEOS Gebäude 3. Etage Lecture
wöchentlich Do 12:00 - 14:00 Externer Ort: NEOS Gebäude 3. Etage Exercise

Die Veranstaltung findet im NEOS Gebäude statt.

Prof. Dr. Christof Büskens
03-M-SP-32Spectral Theory (in englischer Sprache)

Vorlesung
ECTS: 9

Termine:
wöchentlich Mi 14:00 - 16:00 MZH 4140 Lecture
wöchentlich Do 10:00 - 12:00 MZH 4140 Lecture
wöchentlich Do 16:00 - 18:00 MZH 4140 Exercise
PD Dr. Hendrik Vogt
03-M-SP-34Differential Geometry (in englischer Sprache)

Vorlesung
ECTS: 9

Termine:
wöchentlich Di 10:00 - 12:00 MZH 1110 MZH 4140 Lecture
wöchentlich Di 12:00 - 14:00 MZH 1470 Exercise
wöchentlich Mi 16:00 - 18:00 MZH 4140 Lecture

This course will cover manifolds, vector bundles, embeddings and submersions, integral curves and flows, basics of Lie groups, differential forms and integration, Riemannian metrics, geodesics, connections, curvature, and further topics.

Prof. Dr. Anke Dorothea Pohl
03-M-SP-35Selected Topics in Convex Optimization (in englischer Sprache)

Vorlesung
ECTS: 9

Termine:
wöchentlich Mo 10:00 - 12:00 MZH 2340 Lecture
wöchentlich Mi 10:00 - 12:00 MZH 2340 Lecture
wöchentlich Mi 12:00 - 14:00 MZH 2490 (Seminarraum) Exercise

The course will discuss convex optimisation problems and present and analyse algorithms that solve them. Topics will include proximal splitting, acceleration, stochastic algorithms, and performance estimation.

Sebastian Banert
Dirk Lorenz
03-M-SP-36Selected Topics on Optimization for Machine Learning (in englischer Sprache)

Vorlesung
ECTS: 9

Termine:
wöchentlich Do 14:00 - 16:00 MZH 2340 Lecture
wöchentlich Fr 10:00 - 12:00 MZH 2340 Lecture
wöchentlich Fr 12:00 - 14:00 MZH 2340 Exercise
Dirk Lorenz
Lionel Ngoupeyou Tondji

Module: Advanced Communications B (2 x 4,5 CP = 9 CP)

Compulsory module in the area of diversification and in which you must attend a total of two seminars with 4,5 CP each. This semester you can choose from the following seminars:
VAKTitel der VeranstaltungDozentIn
03-M-AC-21Deep Learning for Inverse Problems (in englischer Sprache)

Seminar
ECTS: 4,5/6

Termine:
wöchentlich Mo 14:00 - 16:00 MZH 2340 Seminar
Peter Maaß
03-M-AC-22Advanced Communication Analysis (in englischer Sprache)

Seminar
ECTS: 4,5/6

Termine:
wöchentlich Mi 12:00 - 14:00 MZH 4140 Seminar

Einzeltermine:
Fr 24.05.24 12:00 - 16:00 MZH 1380/1400

In the Seminar Analysis advanced topics in the area of analysis are discussed. The precise topic for Summer semester 2024 will be decided upon with the participants

Prof. Dr. Anke Dorothea Pohl
03-M-AC-23Advanced Robust Control (in englischer Sprache)

Seminar
ECTS: 4,5 / 6

Termine:
wöchentlich Do 10:00 - 12:00 MZH 2340 Seminar
Dr. Chathura Wanigasekara
03-M-AC-28Advanced Numerical Methods for Partial Differential Equations (in englischer Sprache)

Seminar
ECTS: 4,5 / 6

Termine:
wöchentlich Mo 16:00 - 18:00 MZH 2340 Seminar

Seminar on advanced numerical methods for partial differential equations

Alfred Schmidt

Module: Reading Course A (9 CP)

Compulsory module in the area of specialization and with the following course:
VAKTitel der VeranstaltungDozentIn
03-M-RC-STSReading Course Statistics/Stochastics (in englischer Sprache)

Seminar
ECTS: 9

The reading course introduces students to specific topics that may be relevant for the Master's thesis, using mainly original English-language literature (scientific articles and reference books). Students are expected to prepare a seminar talk and an elaboration on the topic.

Prof. Dr. Werner Brannath
Prof. Dr. Thorsten-Ingo Dickhaus

Module: Reading Course B (9 CP)

Compulsory module either in the area of specialization or area of diversification and with the following courses:
VAKTitel der VeranstaltungDozentIn
03-M-RC-ALGReading Course Algebra (in englischer Sprache)

Seminar
ECTS: 9
Prof. Dr. Dmitry Feichtner-Kozlov
03-M-RC-ANAReading Course Analysis (in englischer Sprache)

Seminar
ECTS: 9

Einzeltermine:
Do 13.06.24 08:00 - 10:00 MZH 4140

In the Reading Course Analysis advanced topics in the area of analysis are discussed. The precise topic for Summer semester 2024 will be decided upon with the participants.

Prof. Dr. Anke Dorothea Pohl
03-M-RC-NUMReading Course Numerical Analysis (in englischer Sprache)

Seminar
ECTS: 9

Homepage zur Veranstaltung: http://zetem.uni-bremen.de/o2c/veranstaltungen

Analytical and structured thinking, exact formulation of mathematical facts, comprehension of mathematical proofs and learning of proof techniques, independent and creative solving of mathematical problems, knowledge of real analysis, algorithmic approach to solving mathematical problems.

Prof. Dr. Christof Büskens
03-M-RC-STSReading Course Statistics/Stochastics (in englischer Sprache)

Seminar
ECTS: 9

The reading course introduces students to specific topics that may be relevant for the Master's thesis, using mainly original English-language literature (scientific articles and reference books). Students are expected to prepare a seminar talk and an elaboration on the topic.

Prof. Dr. Werner Brannath
Prof. Dr. Thorsten-Ingo Dickhaus

Mathematik, B.Sc.

General Studies - Fachergänzende Studien

Fachergänzendes Studienangebot aus der Mathematik bzw. Industriemathematik
VAKTitel der VeranstaltungDozentIn
03-IBFW-HTO (03-BE-699.12)Hands-on Tutorial on Optimization (in englischer Sprache)

Blockveranstaltung
ECTS: 3

Einzeltermine:
Mo 23.09.24 - Fr 27.09.24 (Mo, Di, Mi, Do, Fr) 09:00 - 17:00 MZH 5500

https://lvb.informatik.uni-bremen.de/igs/03-ibfw-hto.pdf
A large number of problems arising in practical scenarios like communication, transportation, planning, logistics etc. can be formulated as discrete linear optimization problems. This course briefly introduces the theory of such problems. We develop a toolkit to model real-world problems as (discrete) linear programs. We also explore several ways to find integer solutions such as cutting planes, branch & bound, and column generation.

Throughout the course, we learn these skills by modeling and solving, for example, scheduling, packing, matching, routing, and network-design problems. We focus on translating practical examples into mixed-integer linear programs. We learn how to use solvers (such as CPLEX and Gurobi) and tailor the solution process to certain properties of the problem.

This course consists of two phases:

  • One week Mon-Fri (full day, 9-5) of lectures and practical labs: September 23-27, in MZH.
  • A subsequent project period: One problem has to be modeled, implemented, and solved individually or in a group of at most three students. The topic will be provided by the lecturers and will be discussed on the last day of the block course. The project including the implementation has to be presented in the beginning of the winter semester.

There are no prerequisites except some basic programming skills to participate.

Prof. Dr. Nicole Megow
03-M-GS-7Introduction to R (in englischer Sprache)

Vorlesung
ECTS: 3

Termine:
wöchentlich Fr 10:00 - 13:00 GW1 A0150 Seminar

3 SWS Seminar
Raum wird nach Anmeldung in Stud.IP bekannt gegeben.
Homepage des KKSB und Uni-Lageplan

Prof. Dr. Werner Brannath
Eike Voß
SZHB 0622ONLINE: English for Mathematicians and Industrial Mathematicians (Zertifikatskurs UNIcert II) (B2.3) (in englischer Sprache)
Eingangsniveau: B2.2

Kurs
ECTS: 3

Termine:
wöchentlich Di 16:15 - 17:55 Externer Ort: Onlinekurs (2 SWS)


Edwin Shillington

Mathematik, B.Sc./M.Sc. (Studienbeginn vor 2022)

Master: Wahlpflichtveranstaltungen

Vertiefungsrichtung Algebra

VAKTitel der VeranstaltungDozentIn
03-IMAT-APX (03-ME-602.99a)Approximation Algorithms (in englischer Sprache)

Kurs
ECTS: 6

Termine:
wöchentlich Di 10:00 - 12:00 MZH 3150 Kurs
wöchentlich Do 14:00 - 16:00 MZH 1470 MZH 5500 Übung

Profil: SQ, KIKR.
Schwerpunkt: IMA-SQ, IMVT-AI, IMVT-VMC
weitere Studiengänge: M-M-Alg-Num, M-T
https://lvb.informatik.uni-bremen.de/imat/03-imat-apx.pdf

A large number of problems arising in practical scenarios like communication, transportation, planning, logistics etc. can be modeled as combinatorial optimization problems. In most cases, these problems are computationally intractable and one often resorts to heuristics that provide sufficiently good solutions in reasonable amount of runtime. However, in most cases, such heuristics do not provide a worst case guarantee on the performance in comparison to the optimum solution. In this course, we shall study algorithms for combinatorial optimization problems which can provide strong mathematical guarantees on performance. The course aims at developing a toolkit for solving such problems. The lectures will consist of designing polynomial-time algorithms and proving rigorous bounds on their worst case performances.
We review many classical results in the field of approximation algorithms, highlighting different techniques commonly used for the design of such algorithms. Among others, we will treat the following topics:
• Greedy algorithms and Local Search
• Rounding Data and Dynamic Programming
• Deterministic Rounding of Linear Programs (LPs)
• Random Sampling and Randomized Rounding of LPs
• Primal-Dual Methods
• Hardness of Approximation
• Problem Solving under Uncertainty

Dr. Felix Christian Hommelsheim
03-M-SP-15Analytic and Discrete Convex Geometry (in englischer Sprache)

Vorlesung
ECTS: 9

Termine:
wöchentlich Mo 12:00 - 14:00 MZH 4140 Lecture
wöchentlich Mi 10:00 - 12:00 MZH 1100 MZH 5220 (Didaktik-Labor) Lecture
wöchentlich Mi 12:00 - 14:00 MZH 3150 Exercise

Convex Geometry plays an essential role in several branches of Mathematics, from Discrete Mathematics to Harmonic Analysis. We will discuss some major analytic and discrete aspects of convex geometry and some applications. Our topics will range from the boundary structure of convex bodies, particularly polytopes, to Hadwiger's volume characterisation, via geometric and functional inequalities, as well as geometric and analytic symmetrization techniques.

Eugenia Saorin Gomez

Vertiefungsrichtung Analysis

VAKTitel der VeranstaltungDozentIn
03-M-SP-16Mathematical Foundations of Machine Learning (in englischer Sprache)

Vorlesung
ECTS: 9

Termine:
wöchentlich Mo 12:00 - 14:00 MZH 2340 Lecture
wöchentlich Di 12:00 - 14:00 MZH 2340 Lecture
wöchentlich Di 14:00 - 16:00 MZH 2340 Exercise

This course deals with the mathematical foundations of machine learning with a strong focus on classical theory and well-established algorithms like, for example, support vector machines for classification, ridge regression, principal component analysis for dimensionality reduction and k-means clustering. In addition, deep learning with neural networks will be briefly discussed towards the end of the course.

Peter Maaß
Dr. Matthias Beckmann
03-M-SP-32Spectral Theory (in englischer Sprache)

Vorlesung
ECTS: 9

Termine:
wöchentlich Mi 14:00 - 16:00 MZH 4140 Lecture
wöchentlich Do 10:00 - 12:00 MZH 4140 Lecture
wöchentlich Do 16:00 - 18:00 MZH 4140 Exercise
PD Dr. Hendrik Vogt
03-M-SP-34Differential Geometry (in englischer Sprache)

Vorlesung
ECTS: 9

Termine:
wöchentlich Di 10:00 - 12:00 MZH 1110 MZH 4140 Lecture
wöchentlich Di 12:00 - 14:00 MZH 1470 Exercise
wöchentlich Mi 16:00 - 18:00 MZH 4140 Lecture

This course will cover manifolds, vector bundles, embeddings and submersions, integral curves and flows, basics of Lie groups, differential forms and integration, Riemannian metrics, geodesics, connections, curvature, and further topics.

Prof. Dr. Anke Dorothea Pohl

Vertiefungsrichtung Numerik

VAKTitel der VeranstaltungDozentIn
03-IMAT-APX (03-ME-602.99a)Approximation Algorithms (in englischer Sprache)

Kurs
ECTS: 6

Termine:
wöchentlich Di 10:00 - 12:00 MZH 3150 Kurs
wöchentlich Do 14:00 - 16:00 MZH 1470 MZH 5500 Übung

Profil: SQ, KIKR.
Schwerpunkt: IMA-SQ, IMVT-AI, IMVT-VMC
weitere Studiengänge: M-M-Alg-Num, M-T
https://lvb.informatik.uni-bremen.de/imat/03-imat-apx.pdf

A large number of problems arising in practical scenarios like communication, transportation, planning, logistics etc. can be modeled as combinatorial optimization problems. In most cases, these problems are computationally intractable and one often resorts to heuristics that provide sufficiently good solutions in reasonable amount of runtime. However, in most cases, such heuristics do not provide a worst case guarantee on the performance in comparison to the optimum solution. In this course, we shall study algorithms for combinatorial optimization problems which can provide strong mathematical guarantees on performance. The course aims at developing a toolkit for solving such problems. The lectures will consist of designing polynomial-time algorithms and proving rigorous bounds on their worst case performances.
We review many classical results in the field of approximation algorithms, highlighting different techniques commonly used for the design of such algorithms. Among others, we will treat the following topics:
• Greedy algorithms and Local Search
• Rounding Data and Dynamic Programming
• Deterministic Rounding of Linear Programs (LPs)
• Random Sampling and Randomized Rounding of LPs
• Primal-Dual Methods
• Hardness of Approximation
• Problem Solving under Uncertainty

Dr. Felix Christian Hommelsheim
03-M-SP-12High-Performance-Visualisierung (in englischer Sprache)
High-Performance Visualization
Interaktive Exploration zur Analyse von extrem großen wissenschaftlichen Daten

Vorlesung
ECTS: 4,5 / 6

Termine:
wöchentlich Do 14:00 - 16:00 MZH 1110 Lecture and Exercise

Einzeltermine:
Do 11.07.24 14:00 - 18:00 MZH 1110
Do 22.08.24 - Fr 23.08.24 (Do, Fr) 08:00 - 14:00 MZH 5500

The lecture addresses Interactive Visualization of Huge Scientific Datasets. More information can also be found on the Homepage: https://www.uni-bremen.de/ag-high-performance-visualization

Die Vorlesung beschäftigt sich mit den mathematischen Grundlagen der wissenschaftlichen Visualisierung und behandelt Methoden für das parallele Post-Processing großer wissenschaftlicher Datensätze. Anwendungsbeispiele werden anhand der Open-Source-Software ParaView erläutert.
Homepage zur Veranstaltung: https://www.uni-bremen.de/ag-high-performance-visualization

Prof. Dr. Andreas Gerndt
03-M-SP-14Scientific Programming and Advanced Numerical Methods - an Introduction with Case Studies (in englischer Sprache)

Vorlesung
ECTS: 9

Termine:
wöchentlich Mi 14:00 - 16:00 MZH 2340 Lecture
wöchentlich Do 12:00 - 14:00 MZH 2340 Lecture

Einzeltermine:
Mi 10.07.24 14:00 - 16:00 ZOOM
Mi 17.07.24 14:00 - 16:00 ZOOM
Mo 22.07.24 - Fr 26.07.24 (Mo, Di, Mi, Do, Fr) 10:00 - 16:30

This course provides an introduction to the practice of scientific programming.

Alfred Schmidt
Prof. Dr. Stephan Frickenhaus
03-M-SP-16Mathematical Foundations of Machine Learning (in englischer Sprache)

Vorlesung
ECTS: 9

Termine:
wöchentlich Mo 12:00 - 14:00 MZH 2340 Lecture
wöchentlich Di 12:00 - 14:00 MZH 2340 Lecture
wöchentlich Di 14:00 - 16:00 MZH 2340 Exercise

This course deals with the mathematical foundations of machine learning with a strong focus on classical theory and well-established algorithms like, for example, support vector machines for classification, ridge regression, principal component analysis for dimensionality reduction and k-means clustering. In addition, deep learning with neural networks will be briefly discussed towards the end of the course.

Peter Maaß
Dr. Matthias Beckmann
03-M-SP-20Digital Optimal Control and Optimal Feedback Control (in englischer Sprache)

Vorlesung
ECTS: 9

Termine:
wöchentlich Mo 10:00 - 12:00 Externer Ort: NEOS Gebäude 3. Etage Lecture
wöchentlich Do 10:00 - 12:00 Externer Ort: NEOS Gebäude 3. Etage Lecture
wöchentlich Do 12:00 - 14:00 Externer Ort: NEOS Gebäude 3. Etage Exercise

Die Veranstaltung findet im NEOS Gebäude statt.

Prof. Dr. Christof Büskens
03-M-SP-35Selected Topics in Convex Optimization (in englischer Sprache)

Vorlesung
ECTS: 9

Termine:
wöchentlich Mo 10:00 - 12:00 MZH 2340 Lecture
wöchentlich Mi 10:00 - 12:00 MZH 2340 Lecture
wöchentlich Mi 12:00 - 14:00 MZH 2490 (Seminarraum) Exercise

The course will discuss convex optimisation problems and present and analyse algorithms that solve them. Topics will include proximal splitting, acceleration, stochastic algorithms, and performance estimation.

Sebastian Banert
Dirk Lorenz
03-M-SP-36Selected Topics on Optimization for Machine Learning (in englischer Sprache)

Vorlesung
ECTS: 9

Termine:
wöchentlich Do 14:00 - 16:00 MZH 2340 Lecture
wöchentlich Fr 10:00 - 12:00 MZH 2340 Lecture
wöchentlich Fr 12:00 - 14:00 MZH 2340 Exercise
Dirk Lorenz
Lionel Ngoupeyou Tondji

Vertiefungsrichtung Stochastik & Statistik

VAKTitel der VeranstaltungDozentIn
03-M-SP-22Linear and Generalized Linear Regression (Statistics II) (in englischer Sprache)

Vorlesung
ECTS: 9

Termine:
wöchentlich Mi 08:00 - 10:00 MZH 7200 Lecture
wöchentlich Mi 10:00 - 12:00 MZH 7200 Exercise
wöchentlich Do 08:00 - 10:00 MZH 7200 Lecture

Einzeltermine:
Do 25.07.24 10:00 - 12:00 MZH 7200
Maryam Movahedifar
03-M-SP-33Semiparametric Models (in englischer Sprache)

Vorlesung
ECTS: 9

Termine:
wöchentlich Di 09:00 - 10:30 Vorlesung
wöchentlich Mi 14:00 - 16:00 Übung
wöchentlich Fr 12:30 - 14:00 Vorlesung

Die Veranstaltung findet im KKSB statt.

The course will provide an introduction into the theory of semiparametric models. We will introduce and discuss the mathematical statistical theory for such models and will illustrate the utility of semiparametric models with a number of concrete models and data examples. Hence, the lecture and exercises will cover theoretical and practical aspects of semiparametric models. We will use the open statistical software R for the data applications.

Prof. Dr. Werner Brannath

Master: Seminare

Vertiefungsrichtung Analysis

VAKTitel der VeranstaltungDozentIn
03-M-AC-22Advanced Communication Analysis (in englischer Sprache)

Seminar
ECTS: 4,5/6

Termine:
wöchentlich Mi 12:00 - 14:00 MZH 4140 Seminar

Einzeltermine:
Fr 24.05.24 12:00 - 16:00 MZH 1380/1400

In the Seminar Analysis advanced topics in the area of analysis are discussed. The precise topic for Summer semester 2024 will be decided upon with the participants

Prof. Dr. Anke Dorothea Pohl

Vertiefungsrichtung Numerik

VAKTitel der VeranstaltungDozentIn
03-M-AC-21Deep Learning for Inverse Problems (in englischer Sprache)

Seminar
ECTS: 4,5/6

Termine:
wöchentlich Mo 14:00 - 16:00 MZH 2340 Seminar
Peter Maaß
03-M-AC-23Advanced Robust Control (in englischer Sprache)

Seminar
ECTS: 4,5 / 6

Termine:
wöchentlich Do 10:00 - 12:00 MZH 2340 Seminar
Dr. Chathura Wanigasekara
03-M-AC-28Advanced Numerical Methods for Partial Differential Equations (in englischer Sprache)

Seminar
ECTS: 4,5 / 6

Termine:
wöchentlich Mo 16:00 - 18:00 MZH 2340 Seminar

Seminar on advanced numerical methods for partial differential equations

Alfred Schmidt

Master: Reading Courses

VAKTitel der VeranstaltungDozentIn
03-M-RC-ALGReading Course Algebra (in englischer Sprache)

Seminar
ECTS: 9
Prof. Dr. Dmitry Feichtner-Kozlov
03-M-RC-ANAReading Course Analysis (in englischer Sprache)

Seminar
ECTS: 9

Einzeltermine:
Do 13.06.24 08:00 - 10:00 MZH 4140

In the Reading Course Analysis advanced topics in the area of analysis are discussed. The precise topic for Summer semester 2024 will be decided upon with the participants.

Prof. Dr. Anke Dorothea Pohl
03-M-RC-NUMReading Course Numerical Analysis (in englischer Sprache)

Seminar
ECTS: 9

Homepage zur Veranstaltung: http://zetem.uni-bremen.de/o2c/veranstaltungen

Analytical and structured thinking, exact formulation of mathematical facts, comprehension of mathematical proofs and learning of proof techniques, independent and creative solving of mathematical problems, knowledge of real analysis, algorithmic approach to solving mathematical problems.

Prof. Dr. Christof Büskens
03-M-RC-STSReading Course Statistics/Stochastics (in englischer Sprache)

Seminar
ECTS: 9

The reading course introduces students to specific topics that may be relevant for the Master's thesis, using mainly original English-language literature (scientific articles and reference books). Students are expected to prepare a seminar talk and an elaboration on the topic.

Prof. Dr. Werner Brannath
Prof. Dr. Thorsten-Ingo Dickhaus

Oberseminare

VAKTitel der VeranstaltungDozentIn
Oberseminar Mathematical Parameter Identification (RTG-Seminar) (in englischer Sprache)
Research Seminar - Mathematical Parameter Identification (RTG)

Seminar

Termine:
wöchentlich Mi 12:00 - 14:00 MZH 2340


Dr. rer. nat. Pascal Fernsel

General Studies

VAKTitel der VeranstaltungDozentIn
03-IBFW-HTO (03-BE-699.12)Hands-on Tutorial on Optimization (in englischer Sprache)

Blockveranstaltung
ECTS: 3

Einzeltermine:
Mo 23.09.24 - Fr 27.09.24 (Mo, Di, Mi, Do, Fr) 09:00 - 17:00 MZH 5500

https://lvb.informatik.uni-bremen.de/igs/03-ibfw-hto.pdf
A large number of problems arising in practical scenarios like communication, transportation, planning, logistics etc. can be formulated as discrete linear optimization problems. This course briefly introduces the theory of such problems. We develop a toolkit to model real-world problems as (discrete) linear programs. We also explore several ways to find integer solutions such as cutting planes, branch & bound, and column generation.

Throughout the course, we learn these skills by modeling and solving, for example, scheduling, packing, matching, routing, and network-design problems. We focus on translating practical examples into mixed-integer linear programs. We learn how to use solvers (such as CPLEX and Gurobi) and tailor the solution process to certain properties of the problem.

This course consists of two phases:

  • One week Mon-Fri (full day, 9-5) of lectures and practical labs: September 23-27, in MZH.
  • A subsequent project period: One problem has to be modeled, implemented, and solved individually or in a group of at most three students. The topic will be provided by the lecturers and will be discussed on the last day of the block course. The project including the implementation has to be presented in the beginning of the winter semester.

There are no prerequisites except some basic programming skills to participate.

Prof. Dr. Nicole Megow
03-M-GS-7Introduction to R (in englischer Sprache)

Vorlesung
ECTS: 3

Termine:
wöchentlich Fr 10:00 - 13:00 GW1 A0150 Seminar

3 SWS Seminar
Raum wird nach Anmeldung in Stud.IP bekannt gegeben.
Homepage des KKSB und Uni-Lageplan

Prof. Dr. Werner Brannath
Eike Voß
SZHB 0622ONLINE: English for Mathematicians and Industrial Mathematicians (Zertifikatskurs UNIcert II) (B2.3) (in englischer Sprache)
Eingangsniveau: B2.2

Kurs
ECTS: 3

Termine:
wöchentlich Di 16:15 - 17:55 Externer Ort: Onlinekurs (2 SWS)


Edwin Shillington

Medical Biometry / Biostatistics, M.Sc.

Wahlbereich

VAKTitel der VeranstaltungDozentIn
03-M-SP-22Linear and Generalized Linear Regression (Statistics II) (in englischer Sprache)

Vorlesung
ECTS: 9

Termine:
wöchentlich Mi 08:00 - 10:00 MZH 7200 Lecture
wöchentlich Mi 10:00 - 12:00 MZH 7200 Exercise
wöchentlich Do 08:00 - 10:00 MZH 7200 Lecture

Einzeltermine:
Do 25.07.24 10:00 - 12:00 MZH 7200
Maryam Movahedifar
03-M-SP-33Semiparametric Models (in englischer Sprache)

Vorlesung
ECTS: 9

Termine:
wöchentlich Di 09:00 - 10:30 Vorlesung
wöchentlich Mi 14:00 - 16:00 Übung
wöchentlich Fr 12:30 - 14:00 Vorlesung

Die Veranstaltung findet im KKSB statt.

The course will provide an introduction into the theory of semiparametric models. We will introduce and discuss the mathematical statistical theory for such models and will illustrate the utility of semiparametric models with a number of concrete models and data examples. Hence, the lecture and exercises will cover theoretical and practical aspects of semiparametric models. We will use the open statistical software R for the data applications.

Prof. Dr. Werner Brannath

Sonstige Veranstaltungen

VAKTitel der VeranstaltungDozentIn
03-M-GS-7Introduction to R (in englischer Sprache)

Vorlesung
ECTS: 3

Termine:
wöchentlich Fr 10:00 - 13:00 GW1 A0150 Seminar

3 SWS Seminar
Raum wird nach Anmeldung in Stud.IP bekannt gegeben.
Homepage des KKSB und Uni-Lageplan

Prof. Dr. Werner Brannath
Eike Voß

Technomathematik, B.Sc./M.Sc. (Studienbeginn vor 2022)

Master: Pflichtveranstaltungen

VAKTitel der VeranstaltungDozentIn
03-M-MP-1Modeling Project (Part 1) (in englischer Sprache)

Seminar
ECTS: 6

Termine:
wöchentlich Di 10:00 - 12:00 MZH 2340 Seminar

Over the course of two semesters, the participants of the modeling project work in teams on a project in which they are supposed to use the mathematical knowledge they have already acquired in applications outside of mathematics. The project partners can be industrial companies or research institutes.

Tobias Kluth
Peter Maaß

Master: Wahlpflichtveranstaltungen

VAKTitel der VeranstaltungDozentIn
03-IMAT-APX (03-ME-602.99a)Approximation Algorithms (in englischer Sprache)

Kurs
ECTS: 6

Termine:
wöchentlich Di 10:00 - 12:00 MZH 3150 Kurs
wöchentlich Do 14:00 - 16:00 MZH 1470 MZH 5500 Übung

Profil: SQ, KIKR.
Schwerpunkt: IMA-SQ, IMVT-AI, IMVT-VMC
weitere Studiengänge: M-M-Alg-Num, M-T
https://lvb.informatik.uni-bremen.de/imat/03-imat-apx.pdf

A large number of problems arising in practical scenarios like communication, transportation, planning, logistics etc. can be modeled as combinatorial optimization problems. In most cases, these problems are computationally intractable and one often resorts to heuristics that provide sufficiently good solutions in reasonable amount of runtime. However, in most cases, such heuristics do not provide a worst case guarantee on the performance in comparison to the optimum solution. In this course, we shall study algorithms for combinatorial optimization problems which can provide strong mathematical guarantees on performance. The course aims at developing a toolkit for solving such problems. The lectures will consist of designing polynomial-time algorithms and proving rigorous bounds on their worst case performances.
We review many classical results in the field of approximation algorithms, highlighting different techniques commonly used for the design of such algorithms. Among others, we will treat the following topics:
• Greedy algorithms and Local Search
• Rounding Data and Dynamic Programming
• Deterministic Rounding of Linear Programs (LPs)
• Random Sampling and Randomized Rounding of LPs
• Primal-Dual Methods
• Hardness of Approximation
• Problem Solving under Uncertainty

Dr. Felix Christian Hommelsheim
03-M-SP-12High-Performance-Visualisierung (in englischer Sprache)
High-Performance Visualization
Interaktive Exploration zur Analyse von extrem großen wissenschaftlichen Daten

Vorlesung
ECTS: 4,5 / 6

Termine:
wöchentlich Do 14:00 - 16:00 MZH 1110 Lecture and Exercise

Einzeltermine:
Do 11.07.24 14:00 - 18:00 MZH 1110
Do 22.08.24 - Fr 23.08.24 (Do, Fr) 08:00 - 14:00 MZH 5500

The lecture addresses Interactive Visualization of Huge Scientific Datasets. More information can also be found on the Homepage: https://www.uni-bremen.de/ag-high-performance-visualization

Die Vorlesung beschäftigt sich mit den mathematischen Grundlagen der wissenschaftlichen Visualisierung und behandelt Methoden für das parallele Post-Processing großer wissenschaftlicher Datensätze. Anwendungsbeispiele werden anhand der Open-Source-Software ParaView erläutert.
Homepage zur Veranstaltung: https://www.uni-bremen.de/ag-high-performance-visualization

Prof. Dr. Andreas Gerndt
03-M-SP-14Scientific Programming and Advanced Numerical Methods - an Introduction with Case Studies (in englischer Sprache)

Vorlesung
ECTS: 9

Termine:
wöchentlich Mi 14:00 - 16:00 MZH 2340 Lecture
wöchentlich Do 12:00 - 14:00 MZH 2340 Lecture

Einzeltermine:
Mi 10.07.24 14:00 - 16:00 ZOOM
Mi 17.07.24 14:00 - 16:00 ZOOM
Mo 22.07.24 - Fr 26.07.24 (Mo, Di, Mi, Do, Fr) 10:00 - 16:30

This course provides an introduction to the practice of scientific programming.

Alfred Schmidt
Prof. Dr. Stephan Frickenhaus
03-M-SP-15Analytic and Discrete Convex Geometry (in englischer Sprache)

Vorlesung
ECTS: 9

Termine:
wöchentlich Mo 12:00 - 14:00 MZH 4140 Lecture
wöchentlich Mi 10:00 - 12:00 MZH 1100 MZH 5220 (Didaktik-Labor) Lecture
wöchentlich Mi 12:00 - 14:00 MZH 3150 Exercise

Convex Geometry plays an essential role in several branches of Mathematics, from Discrete Mathematics to Harmonic Analysis. We will discuss some major analytic and discrete aspects of convex geometry and some applications. Our topics will range from the boundary structure of convex bodies, particularly polytopes, to Hadwiger's volume characterisation, via geometric and functional inequalities, as well as geometric and analytic symmetrization techniques.

Eugenia Saorin Gomez
03-M-SP-16Mathematical Foundations of Machine Learning (in englischer Sprache)

Vorlesung
ECTS: 9

Termine:
wöchentlich Mo 12:00 - 14:00 MZH 2340 Lecture
wöchentlich Di 12:00 - 14:00 MZH 2340 Lecture
wöchentlich Di 14:00 - 16:00 MZH 2340 Exercise

This course deals with the mathematical foundations of machine learning with a strong focus on classical theory and well-established algorithms like, for example, support vector machines for classification, ridge regression, principal component analysis for dimensionality reduction and k-means clustering. In addition, deep learning with neural networks will be briefly discussed towards the end of the course.

Peter Maaß
Dr. Matthias Beckmann
03-M-SP-20Digital Optimal Control and Optimal Feedback Control (in englischer Sprache)

Vorlesung
ECTS: 9

Termine:
wöchentlich Mo 10:00 - 12:00 Externer Ort: NEOS Gebäude 3. Etage Lecture
wöchentlich Do 10:00 - 12:00 Externer Ort: NEOS Gebäude 3. Etage Lecture
wöchentlich Do 12:00 - 14:00 Externer Ort: NEOS Gebäude 3. Etage Exercise

Die Veranstaltung findet im NEOS Gebäude statt.

Prof. Dr. Christof Büskens
03-M-SP-22Linear and Generalized Linear Regression (Statistics II) (in englischer Sprache)

Vorlesung
ECTS: 9

Termine:
wöchentlich Mi 08:00 - 10:00 MZH 7200 Lecture
wöchentlich Mi 10:00 - 12:00 MZH 7200 Exercise
wöchentlich Do 08:00 - 10:00 MZH 7200 Lecture

Einzeltermine:
Do 25.07.24 10:00 - 12:00 MZH 7200
Maryam Movahedifar
03-M-SP-32Spectral Theory (in englischer Sprache)

Vorlesung
ECTS: 9

Termine:
wöchentlich Mi 14:00 - 16:00 MZH 4140 Lecture
wöchentlich Do 10:00 - 12:00 MZH 4140 Lecture
wöchentlich Do 16:00 - 18:00 MZH 4140 Exercise
PD Dr. Hendrik Vogt
03-M-SP-33Semiparametric Models (in englischer Sprache)

Vorlesung
ECTS: 9

Termine:
wöchentlich Di 09:00 - 10:30 Vorlesung
wöchentlich Mi 14:00 - 16:00 Übung
wöchentlich Fr 12:30 - 14:00 Vorlesung

Die Veranstaltung findet im KKSB statt.

The course will provide an introduction into the theory of semiparametric models. We will introduce and discuss the mathematical statistical theory for such models and will illustrate the utility of semiparametric models with a number of concrete models and data examples. Hence, the lecture and exercises will cover theoretical and practical aspects of semiparametric models. We will use the open statistical software R for the data applications.

Prof. Dr. Werner Brannath
03-M-SP-34Differential Geometry (in englischer Sprache)

Vorlesung
ECTS: 9

Termine:
wöchentlich Di 10:00 - 12:00 MZH 1110 MZH 4140 Lecture
wöchentlich Di 12:00 - 14:00 MZH 1470 Exercise
wöchentlich Mi 16:00 - 18:00 MZH 4140 Lecture

This course will cover manifolds, vector bundles, embeddings and submersions, integral curves and flows, basics of Lie groups, differential forms and integration, Riemannian metrics, geodesics, connections, curvature, and further topics.

Prof. Dr. Anke Dorothea Pohl
03-M-SP-35Selected Topics in Convex Optimization (in englischer Sprache)

Vorlesung
ECTS: 9

Termine:
wöchentlich Mo 10:00 - 12:00 MZH 2340 Lecture
wöchentlich Mi 10:00 - 12:00 MZH 2340 Lecture
wöchentlich Mi 12:00 - 14:00 MZH 2490 (Seminarraum) Exercise

The course will discuss convex optimisation problems and present and analyse algorithms that solve them. Topics will include proximal splitting, acceleration, stochastic algorithms, and performance estimation.

Sebastian Banert
Dirk Lorenz
03-M-SP-36Selected Topics on Optimization for Machine Learning (in englischer Sprache)

Vorlesung
ECTS: 9

Termine:
wöchentlich Do 14:00 - 16:00 MZH 2340 Lecture
wöchentlich Fr 10:00 - 12:00 MZH 2340 Lecture
wöchentlich Fr 12:00 - 14:00 MZH 2340 Exercise
Dirk Lorenz
Lionel Ngoupeyou Tondji

Master: Seminare

VAKTitel der VeranstaltungDozentIn
03-M-AC-21Deep Learning for Inverse Problems (in englischer Sprache)

Seminar
ECTS: 4,5/6

Termine:
wöchentlich Mo 14:00 - 16:00 MZH 2340 Seminar
Peter Maaß
03-M-AC-22Advanced Communication Analysis (in englischer Sprache)

Seminar
ECTS: 4,5/6

Termine:
wöchentlich Mi 12:00 - 14:00 MZH 4140 Seminar

Einzeltermine:
Fr 24.05.24 12:00 - 16:00 MZH 1380/1400

In the Seminar Analysis advanced topics in the area of analysis are discussed. The precise topic for Summer semester 2024 will be decided upon with the participants

Prof. Dr. Anke Dorothea Pohl
03-M-AC-23Advanced Robust Control (in englischer Sprache)

Seminar
ECTS: 4,5 / 6

Termine:
wöchentlich Do 10:00 - 12:00 MZH 2340 Seminar
Dr. Chathura Wanigasekara
03-M-AC-28Advanced Numerical Methods for Partial Differential Equations (in englischer Sprache)

Seminar
ECTS: 4,5 / 6

Termine:
wöchentlich Mo 16:00 - 18:00 MZH 2340 Seminar

Seminar on advanced numerical methods for partial differential equations

Alfred Schmidt

Oberseminare

VAKTitel der VeranstaltungDozentIn
Oberseminar Mathematical Parameter Identification (RTG-Seminar) (in englischer Sprache)
Research Seminar - Mathematical Parameter Identification (RTG)

Seminar

Termine:
wöchentlich Mi 12:00 - 14:00 MZH 2340


Dr. rer. nat. Pascal Fernsel

General Studies

VAKTitel der VeranstaltungDozentIn
03-IBFW-HTO (03-BE-699.12)Hands-on Tutorial on Optimization (in englischer Sprache)

Blockveranstaltung
ECTS: 3

Einzeltermine:
Mo 23.09.24 - Fr 27.09.24 (Mo, Di, Mi, Do, Fr) 09:00 - 17:00 MZH 5500

https://lvb.informatik.uni-bremen.de/igs/03-ibfw-hto.pdf
A large number of problems arising in practical scenarios like communication, transportation, planning, logistics etc. can be formulated as discrete linear optimization problems. This course briefly introduces the theory of such problems. We develop a toolkit to model real-world problems as (discrete) linear programs. We also explore several ways to find integer solutions such as cutting planes, branch & bound, and column generation.

Throughout the course, we learn these skills by modeling and solving, for example, scheduling, packing, matching, routing, and network-design problems. We focus on translating practical examples into mixed-integer linear programs. We learn how to use solvers (such as CPLEX and Gurobi) and tailor the solution process to certain properties of the problem.

This course consists of two phases:

  • One week Mon-Fri (full day, 9-5) of lectures and practical labs: September 23-27, in MZH.
  • A subsequent project period: One problem has to be modeled, implemented, and solved individually or in a group of at most three students. The topic will be provided by the lecturers and will be discussed on the last day of the block course. The project including the implementation has to be presented in the beginning of the winter semester.

There are no prerequisites except some basic programming skills to participate.

Prof. Dr. Nicole Megow
03-M-GS-7Introduction to R (in englischer Sprache)

Vorlesung
ECTS: 3

Termine:
wöchentlich Fr 10:00 - 13:00 GW1 A0150 Seminar

3 SWS Seminar
Raum wird nach Anmeldung in Stud.IP bekannt gegeben.
Homepage des KKSB und Uni-Lageplan

Prof. Dr. Werner Brannath
Eike Voß
SZHB 0622ONLINE: English for Mathematicians and Industrial Mathematicians (Zertifikatskurs UNIcert II) (B2.3) (in englischer Sprache)
Eingangsniveau: B2.2

Kurs
ECTS: 3

Termine:
wöchentlich Di 16:15 - 17:55 Externer Ort: Onlinekurs (2 SWS)


Edwin Shillington

Systems Engineering, B.Sc. / M.Sc.

VAKTitel der VeranstaltungDozentIn
03-IMAP-AMLAdvanced Machine Learning (in englischer Sprache)

Vorlesung
ECTS: 6

Termine:
wöchentlich Mo 10:00 - 12:00 MZH 6200 Übung
wöchentlich Di 16:00 - 18:00 MZH 1450 Übung
wöchentlich Mi 14:00 - 16:00 MZH 1380/1400 Vorlesung

Profil: KIKR
Schwerpunkt: IMAP-AI, IMA-VMC
https://lvb.informatik.uni-bremen.de/imap/03-imap-aml.pdf

Tanja Schultz
Felix Putze
03-IMAP-RL (03-ME-712.03)Reinforcement Learning (in englischer Sprache)

Kurs
ECTS: 6

Termine:
wöchentlich Di 10:00 - 12:00 DFKI RH1 B0.10 Kurs
wöchentlich Do 16:00 - 18:00 DFKI RH1 B0.10 Kurs

Profil: KIKR.
Schwerpunkt: IMA-AI, IMVP-VMC
https://lvb.informatik.uni-bremen.de/imap/03-imap-rl.pdf

Frank Kirchner
Melvin Laux

Wirtschaftsinformatik, B.Sc.

2./3. Studienjahr

Wahlmodule

Schwerpunkt "Computational Finance"

WI-CF-WP

Auflistung der WInf-Schwerpunkt-Wahlmodule siehe unter WInf-Wahlmodule
VAKTitel der VeranstaltungDozentIn
03-IBAP-ML (03-BB-710.10)Grundlagen des Maschinellen Lernens (in englischer Sprache)
Fundamentals of Machine Learning

Kurs
ECTS: 6

Termine:
wöchentlich Mo 14:00 - 16:00 MZH 1470 Übung
wöchentlich Mi 08:00 - 10:00 MZH 1380/1400 Vorlesung
wöchentlich Mi 10:00 - 12:00 MZH 1380/1400 GW2 B1820 Übung

Einzeltermine:
Mi 12.06.24 08:00 - 09:30 MZH 1380/1400
Di 23.07.24 14:00 - 16:00 NW1 H 1 - H0020

Schwerpunkt: AI
https://lvb.informatik.uni-bremen.de/ibap/03-ibap-ml.pdf
Die Übungen starten in der 2. Semesterwoche.

Tanja Schultz
Felix Putze
Darius Ivucic
Gabriel Ivucic
Zhao Ren

Schwerpunkt "E-Business"

WI-EB-P

VAKTitel der VeranstaltungDozentIn
07-B37-4-13-15Digital Business and Management (in englischer Sprache)

Seminar
ECTS: 6

Termine:
wöchentlich Mo 10:00 - 12:00 WiWi1 A1100
Dr. Phil Hennel

Schwerpunkt "Informationstechnikmanagement"

WI-IM-WP

Auflistung der WInf-Schwerpunkt-Wahlmodule siehe unter WInf-Wahlmodule
VAKTitel der VeranstaltungDozentIn
07-B37-4-13-16Digital Ethics (in englischer Sprache)

Seminar
ECTS: 6

Termine:
wöchentlich Do 08:00 - 10:00 WiWi2 F3290

Einzeltermine:
Do 27.06.24 16:00 - 18:00 DIGITAL
Prof. Dr. Benjamin Müller, MBA

WInf-Wahlmodule

WI-W/11 Data Science

Schwerpunkt: CF
VAKTitel der VeranstaltungDozentIn
03-IBVA-DSV (03-BE-802.98a)Data Science and Visualization (in englischer Sprache)

Kurs
ECTS: 6

Termine:
wöchentlich Mo 10:00 - 12:00 MZH 5600 Kurs
wöchentlich Mo 12:00 - 14:00 MZH 5600 Kurs

Eine Doppelanerkennung von 'Data Science' und 'Data Science and Visualization' ist nicht möglich.
https://lvb.informatik.uni-bremen.de/ibv/03-ibva-dsv.pdf

The class will provide an introduction to data science and information visualization. For this, the programming language Python will be used (and taught). For creating data visualizations, you will be able to choose among a series of tools (e.g., Plotly, Observable, etc.)

We will explore different concepts from the fields of human-computer interaction, data visualization, and computer-supported collaborative work. You will learn about:
      • Basic statistics
      • Visualization techniques
      • Interaction design
Exploratory data analysis and evaluation, as an integral part of data science, will also be taught. The course will involve applying the learned techniques to real-world datasets to develop a custom project.

This class is taught in person and in English. Use material like the coursebook to learn more about the topics as we progress in the course.

Dr. Gabriela Molina Leon

General Studies

VAKTitel der VeranstaltungDozentIn
META-2024-ALL-IF27. internationale Informatica Feminale (in englischer Sprache)
Informatica Feminale - Summer University for Women in Computing
Sommeruniversität für Frauen in der Informatik /Summer University for Women in Computing

Blockveranstaltung
ECTS: 1-3 (je Kurs/for every course)

60 Lehrveranstaltungen in Deutsch und Englisch für Bachelor- und Masterstudentinnen aller Fächer. Als General Studies sowie teilweise als Fachstudium im Sommersemester 2024 sowie im Wintersemester 2024/25 anerkannt. Alle Einzelangaben, Zeiten und Anmeldungen jederzeit nur über die Website https://www.informatica-feminale.de.
60 courses in German and English for women Bachelor and Master students from all fields of study. Courses are part of General Studies, some are accepted in Informatics; in the summer semester 2024 as well as in winter semester 2024/25. Further information, schedules and registration only on the website https://www.informatica-feminale.de.

Veronika Oechtering
Henrike Illig

Weitere Veranstaltungen

VAKTitel der VeranstaltungDozentIn
07-BS37-4-33-01PRAXIS Summer Camp: Praxis hautnah erleben - Kleinprojekte mit Unternehmen (für BA und MA) (in englischer Sprache)
Experience first hand practice - small projects with companies

Seminar
ECTS: 6

Einzeltermine:
Fr 05.04.24 14:00 - 16:00 WiWi1 A1100
Fr 12.04.24 14:00 - 16:00 WiWi1 A1100
Fr 26.07.24 08:00 - 18:00 WiWi1 A1100

Das PRAXIS Summer Camp ist ein sehr praxisorientiertes Lehrformat. Studierende verschiedenster Disziplinen arbeiten in kleinen Teams in einer 3-wöchigen intensiven Arbeitsphase an Projekten aus der Praxis.
Es gibt eine gemeinschaftliche Kick-off Veranstaltung am 29. Juli 2024 und das Finale Event am 16. August 2024, wo alle Gruppen ihre Ergebnisse präsentieren. Da wir auch internationale Studierende mit einbinden, ist die Präsentationssprache Englisch. Dazwischen findet die Projektarbeit in Kleingruppen statt, zum Teil vor Ort im Unternehmen.
Es wird ein Workload von 30 Std./Woche in flexilber Einteilung in Abstimmung mit dem Team erwartet.

Weitere Infos und Timeline:
https://blogs.uni-bremen.de/praxissummercamp
https://www.uni-bremen.de/wiwi/praxis-und-transfer/angebote-fuer-studierende/praxisrelevante-seminare-und-events/praxis-summer-camp

Dipl.-Oec. Maren Hartstock