Dr. Jens Schlöter

About me

I am a research assistant at the University of Bremen  in the group of Prof. Dr. Nicole Megow. I joined the group in October 2019 as a PhD student and succesfully defended my PhD thesis on November 10, 2023. My research interests are optimization under (explorable) uncertainty, learning-augmented algorithms, approximation algorithms, and combinatorial optimization. Your can find a list of my publications down below as well as on scholar and dblp.

Publications

Santa Claus meets Makespan and Matroids: Algorithms and Reductions  arxiv.org 
Étienne Bamas, Alexander Lindermayr, Nicole Megow, Lars Rohwedder, Jens Schlöter
SODA 2024

Minimalistic Predictions to Schedule Jobs with Online Precedence Constraints  arxiv.org
Alexandra Lassota, Alexander Lindermayr, Nicole Megow, Jens Schlöter
ICML 2023.

Sorting and Hypergraph Orientation under Uncertainty with Predictions  arxiv.org
Thomas Erlebach, Murilo Santos de Lima, Nicole Megow, Jens Schlöter
IJCAI 2023.

Set Selection under Explorable Stochastic Uncertainty via Covering Techniques  arxiv.org
Nicole Megow and Jens Schlöter
IPCO 2023.

Learning-Augmented Query Policies for Minimum Spanning Tree with Uncertainty arxiv.org
Thomas Erlebach, Murilo Santos de Lima, Nicole Megow, Jens Schlöter
ESA 2022

Throughput Scheduling with Equal Additive Laxity sciencedirect.com
Martin Böhm, Nicole Megow, Jens Schlöter
Operations Research Letters 

Explorable Uncertainty Meets Decision-Making in Logistics springer.com 
Nicole Megow and Jens Schlöter
Dynamics in Logistics: 35-56, 2021  springer.com 

Robustification of Online Graph Exploration Methods  arxiv.org
Franziska Eberle, Alexander Lindermayr, Nicole Megow, Lukas Nölke, Jens Schlöter
AAAI 2022.

Orienting (Hyper)graphs Under Explorable Stochastic Uncertainty  pdf
Bampis E., Dürr C., Erlebach T., de Lima M.S., Megow N., Schlöter J.
ESA 2021.

Throughput Scheduling with Equal Additive Laxity springer.com
Böhm M., Megow N., Schlöter J.
CIAC 2021

On the Complexity of Conditional DAG Scheduling in Multiprocessor Systems  PDF  ieeexplore.ieee.org
Marchetti-Spaccamela A., Megow N., Schlöter J., Skutella M., Stougie L.
IPDPS 2020.

Improving SAT Solving Using Monte Carlo Tree Search-based Clause Learning  springer.com
Keszöcze O., Schmitz K., Schlöter J., Drechsler R.
In: Rolf Drechsler, Mathias Soeken (Hrsg.): Advanced Boolean Techniques - Selected Papers from the 13th International Workshop on Boolean Problems, Springer International Publishing, 2019.

Theses

Schlöter, J.: Optimization under Explorable Uncertainty: Beyond the Worst-Case PDF
Advisor: Prof. Dr. Nicole Megow,  PhD thesis, University of Bremen, 2023.

Schlöter, J.: Conditional Directed Acyclic Graphs: On the Complexity of Computing the Worst-Case Execution Time  PDF
Advisor: Prof. Dr. Nicole Megow, Master thesis, University of Bremen, 2019.

Schlöter, J.: Modellierung von Scheduling-Problemen mit zeitbehafteten Petri-Netzen  PDF
Advisor: Dr. Sabine Kuske, Bachelor thesis, University of Bremen, 2016.

Teaching

I worked as a teaching assistant for the following lectures and seminars:

• Algorithm Theory (2020, 2022, 2023)

• Operations Research (2020, 2022)

• Algorithmic Discrete Mathematics (2021)

• Hands-on Tutorial on Optimization (2021, 2022, 2023)

• Combinatorial Optimization and Machine Learning (2021)

• Introduction to Technical Computer Science (2016)