About me
Since April 2024, I am a Marie Skłodowska-Curie postdoctoral fellow at Université libre de Bruxelles working on my project NeurExCo: Synergizing Neural Network Theory and Combinatorial Optimization via Extension Complexity advised by Samuel Fiorini. My research interests span various topics across discrete mathematics, theoretical computer science, and machine learning, with an emphasis on applying techniques from polyhedral geometry and combinatorial optimization to neural network theory.
Previously, in the winter semester 2023/24, I was a substitute professor for discrete mathematics at Goethe-Universität Frankfurt, Germany. During that time, I taught a first-semester course Introduction to Computer-Oriented Mathematics and an advanced BSc- and MSc-level seminar Combinatorial (Linear) Algebra and Geometry (both in German).
Before that, I held postdoctoral positions with Samuel Fiorini at Université libre de Bruxelles (2023) and with László Végh at LSE in London (2022-23). I completed my PhD with Martin Skutella at TU Berlin (2018-22), and my BSc and MSc with Sven O. Krumke at TU Kaiserslautern (2013-18).
My brother Johannes is a postdoc in mathematical image processing at University College London.
Accepted Publications
A First Order Method for Linear Programming Parameterized by Circuit Imbalance
with Richard Cole, Yixin Tao, and László A. Végh
Accepted to Conference on Integer Programming and Combinatorial Optimization (IPCO 2024)
Preprint
Mode Connectivity in Auction Design
with Yixin Tao and László A. Végh
Accepted to Conference on Neural Information Processing Systems (NeurIPS 2023)
Preprint
Training Neural Networks is NP-Hard in Fixed Dimension
with Vincent Froese
Accepted to Conference on Neural Information Processing Systems (NeurIPS 2023)
Preprint
Training Fully Connected Neural Networks is ∃R-Complete
with Daniel Bertschinger, Paul Jungeblut, Tillmann Miltzow, and Simon Weber
Accepted to Conference on Neural Information Processing Systems (NeurIPS 2023)
Preprint
Towards Lower Bounds on the Depth of ReLU Neural Networks
with Amitabh Basu, Marco Di Summa, and Martin Skutella
SIAM Journal on Discrete Mathematics (SIDMA 2023)
Conference version at Conference on Neural Information Processing Systems (NeurIPS 2021)
Journal Version |
Conference Version |
Preprint |
Video
Provably Good Solutions to the Knapsack Problem via Neural Networks of Bounded Size
with Martin Skutella
INFORMS Journal on Computing (IJOC 2023)
Conference Version at AAAI 2021 Conference on Artificial Intelligence
Journal Version |
Conference Version |
Preprint |
Video
ReLU Neural Networks of Polynomial Size for Exact Maximum Flow Computation
with Leon Sering
Conference on Integer Programming and Combinatorial Optimization (IPCO 2023)
Conference Version |
Preprint
Lower Bounds on the Depth of Integral ReLU Neural Networks via Lattice Polytopes
with Christian Haase and Georg Loho
International Conference on Learning Representations (ICLR 2023)
Conference Version |
Preprint
The Computational Complexity of ReLU Network Training Parameterized by Data Dimensionality
with Vincent Froese and Rolf Niedermeier
Journal of Artificial Intelligence Research (JAIR 2022)
Journal Version |
Preprint
Online Algorithms to Schedule a Proportionate Flexible Flow Shop of Batching Machines
with Christian Weiß, Heiner Ackermann, Sandy Heydrich, and Sven O. Krumke
Journal of Scheduling (J Sched 2022)
Journal Version |
Preprint
Coloring Drawings of Graphs
with Felix Schröder and Raphael Steiner
Electronic Journal of Combinatorics (E-JC 2022)
Journal Version |
Preprint
Scheduling a Proportionate Flow Shop of Batching Machines
with Christian Weiß, Heiner Ackermann, Sandy Heydrich, and Sven O. Krumke
Journal of Scheduling (J Sched 2020)
Journal Version |
Preprint
Decision Support for Material Procurement
with Heiner Ackermann, Erik Diessel, Michael Helmling, Neil Jami, and Johanna Schneider
Operations Research Proceedings 2019
Conference Version
Sweep Algorithms for the Capacitated Vehicle Routing Problem with Structured Time Windows
with Philipp Hungerländer and Christian Truden
Operations Research Proceedings 2018
Conference Version |
Preprint
Theses
Facets of Neural Network Complexity
PhD Thesis, TU Berlin (2022)
Scheduling a Proportionate Flow Shop of Batching Machines
Master Thesis, TU Kaiserslautern (2018)
Received an award from the German Operations Research Society (GOR)
Summary published in OR Proceedings 2019
A Parametric View on Robust Graph Problems
Bachelor Thesis, TU Kaiserslautern (2016)