teaching

I offer several thesis projects for topics that concern my research. For example, if you are interested in verification, artificial intelligence, machine learning, or probabilistic programming, please contact me! Some topics are listed on the institute webpage</a>, for a full overview just contact me.

Responsible Lecturer and Course Coordinator

Processors: 2017/2018, 2018/2019, 2019/2020, 2020/2021, 2021/2022, 2022/2023

Model Checking: 2017/2018, 2018/2019, 2019/2020, 2020/2021, 2021/2022, 2022/2023

Operating Systems: 2017/2018, 2018/2019, 2019/2020

Finished Bachelor Theses

Koen Verdenius (2021, Bachelor thesis, A POMDP model for safety-critical systems and its deteriorating sensors)

Tom Smitjes (2020, Bachelor thesis, Connecting Mixed-Integer Linear Programming and Finite-memory POMDP Strategies)

Niels van Welzen (2020, Bachelor thesis, An iterative version of Tarjan’s algorithm)

Johan Sijtsma (2020, Creating a formal model of the game 2048)

Sjoerd Hemels (2019, A comparison of model checking tools for synchronisation problems)

Laura Philipse (2019, Routing Algorithms for Autonomous Agricultural Vehicles)

Manuela Bergau (2019, Human-in-the-loop strategy synthesis: PAC-MAN verified)

Marnix Suilen (2018, Convex optimization for uncertain Markov decision processes)

At RWTH Aachen University:

Lukas Westhofen (2016, On-the-fly Model Checking for Probabilistic Programs)

Tim Quatmann (2015, Counterexamples for Expected Rewards)

Matthias Volk (2014, Verification and Synthesis for Parametric Markov Chains)

Finished Master Theses

Pleun Koldewijn (2022, Optimal Order Execution for FX trading)

Marck van der Vegt (2021, Model Learning of Deterministic MDPs)

Serena Rietbergen (2021, History-based Rewards for POMDPs)

Ilse Pool (2021, Optimal Maintenance Strategies for an Industrial Scrubber System)

Reinier Joosse (2021, Evaluating Adversarial Attack Detectors using Formal Verification Methods)

David Kerkkamp (2021, Grouping of Maintenance Actions on Sewer Pipes: Using Deep Reinforcement Learning and Graph Neural Networks)

Nils Neerhof (2021, Formal Verification in Uncertain POMDPs)

Christoph Schmidl (2020, Approximating Black-Box Deep Neural Networks using Active Learning as a Proxy Measurement for Robustness)

Marnix Suilen (2020, Entropy-guided decision making in multiple-environment Markov decision processes)

At RWTH Aachen University:

Marian Van de veire (2014, Minimal Critical Subsystems for Probabilistic Models with Nondeterminism)

Andreas Vorpahl (2014, Compositional Counterexamples for MDPs)~\cite{wimmer-et-al-qest-2013}

Maik Scheffler (2013, Hierarchical Counterexamples for DTMCs – Case Studies)

Amith Belur Nagabushana, (2013, Minimal Critical Subsystems for PCTL Properties of Markov Models)