Matthias Volk

dav
Email
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Address
Room 4205
Ahornstraße 55
D-52074 Aachen
Phone
+49 241 80 21212

Research

I am a PhD student at the Software Modeling and Verification Group (MOVES) headed by Professor J.-P. Katoen since December 2015. I was a doctoral researcher (Stipendiat) within the Research Training Group UnRAVeL since 2017. Since 2020 I am part of the ERC research project FRAPPANT.
My research interests include:

  • Analysis of dynamic fault trees (DFTs)
  • Verifiying fault trees for railway safety (see UnRAVeL project AP4)
  • Model checking of (parametric) probabilistic systems

Tool support

I am actively involved in the development of the following tools:

  • The probabilistic model checker Storm and its python bindings stormpy
  • The python bindings pycarl for the arithmetic library CArL
  • The parameter synthesis framework for parametric Markov chains PROPhESY

Bachelor/Master Theses

I am always looking forward to work with students. If you are looking for a thesis in one of the areas above, do not hesitate to contact me and we can discuss current thesis topics. Some ideas are also given in our list of open topics.

Currently, I am supervising the following theses:

  • Daniel Basgöze, Dynamic Fault Tree Analysis using Binary Decision Diagrams, Bachelor thesis (together with Shahid Khan)
  • Markus Miliats, Analyzing critical components in Dynamic Fault Trees, Bachelor thesis

In the past, I have been supervising the following theses:

Teaching

I am currently involved in the following teaching activities:

Past teaching activities:

Awards

Our paper A DFT Modeling Approach for Infrastructure Reliability Analysis of Railway Station Areas (joint work with Norman Weik, Joost-Pieter Katoen and Nils Nießen) won the Best Paper Award at the 24th International Conference on Formal Methods for Industrial Critical Systems (FMICS) in Amsterdam in 2019. The paper presents a model of railway station areas in terms of dynamic fault trees (DFTs). The DFT model is used to assess the reliability of the infrastructure elements in the station area and the influence of infrastructure failures on the routability options of trains.

Our paper Automated Fine Tuning of Probabilistic Self-Stabilizing Algorithms (joint work with Saba Aflaki, Borzoo Bonakdarpour, Joost-Pieter Katoen and Arne Storjohann) won the Prof. C.V. Ramamoorthy Best Paper Award at the 36th IEEE Int. Symposium on Reliable Distributed Systems (SRDS) in Hongkong in 2017. The paper presents automated techniques to find the probability distribution that achieves minimum average recovery time for randomized distributed self-stabilizing algorithms.