I am a researcher interested in the analysis of safety-critical systems.
I have been an Assistant Professor (UD) at the Software Science Group of the Radboud University in Nijmegen, the Netherlands, since September 2021. Previously, I was a PostDoc at UC Berkeley as part of the Learn and Verify Group headed by Sanjit Seshia. Before, I was a PhD student at RWTH Aachen University, under the supervision of Joost-Pieter Katoen. I defended my PhD thesis titled Parameter Synthesis in Markov Models (pdf) in February 2020.
You can reach me at sjunges?cs.ru.nl.
Broadly, my research is in the analysis of autonomous systems and critical infrastructure. Key aspects of my research cover the computational support for modelling, validation and verification of these systems.
Most of my research is model-based, and I lay particular focus on the algorithmic support for models that explicitly model uncertainty.
More precisely, I often work with probabilistic model checkers and SAT/SMT solvers. I analyze extensions of Markov decision processes (MDPs), in particular also parametric or partially observable MDPs. My research is largely driven by the development and implementation of algorithms.