M.Sc. Pascal Zimmer

About Me

Since January 2022, I am a PhD student at the Chair for Information Security. Before that, I worked as a research assistant at the Chair for Embedded Security at the Ruhr University Bochum and as a visiting researcher at the Embedded Security group of the Max Planck Institute for Security and Privacy. I obtained both my Bachelor’s and Master’s degree at the Ruhr University Bochum in cybersecurity with a focus on wireless physical layer security. 

Research

My research focuses on the robustness of machine learning systems in real-world environments. This includes, but is not limited to, machine-learning-as-a-service (MLaaS), distributed/decentralized learning systems, e.g., federated learning, and deployments in autonomous vehicles or facial recognition systems.

Publications

• Pascal Zimmer, Simon Lachnit, Alexander Jan Zielinski, Ghassan Karame
  Targeted Physical Evasion Attacks in the Near-Infrared Domain
  In Proceedings of the Network and Distributed Systems Security Symposium (NDSS) 2026 [ Preprint ] 
• Sébastien Andreina, Pascal Zimmer, Ghassan Karame
  On the Robustness of Distributed Machine Learning Against Transfer Attacks,
  Proceedings of the AAAI Conference on Artificial Intelligence, 39(15), 15382-15390. 2025. [ PDF | Bibtex ]
• Pascal Zimmer, Sébastien Andreina, Giorgia Marson, Ghassan Karame
  Closing the Gap: Achieving Better Accuracy-Robustness Tradeoffs Against Query-Based Attacks,
  Proceedings of the AAAI Conference on Artificial Intelligence, 38(19), 21859-21868, 2024. [ PDF | BibTex ]

theses supervision

I had the pleasure of co-supervising theses of many talented students in the field of machine learning security. If you are interested in writing a thesis with us, have a look at this page.

• Micha Eyl, “Evaluating Client-Side Purification Techniques for Federated Learning“, M.Sc.
• Pablo Schmücker, “Evaluating defense mechanisms against universal adversarial perturbations for convolutional neural networks“, B.Sc.
• Luis Griepenstroh, “Mitigation Strategies for Real-World Adversarial Patches“, B.Sc.
• Max Randhahn, “Security Analysis of Adversarial Attacks in Federated Learning“, B.Sc.
• Jan Richter, “Security Analysis of Transfer-based Adversarial Attacks in the Graybox Model“, M.Sc.
• Alexander Jan Zielinski, “Imperceptible Adversarial Examples for Autonomous Vehicles“, M.Sc.
• Fabian Rüsen, “Security Analysis of Adversarial Examples in the Graybox Model“, M.Sc.
• Pascal Bongartz, “Cross-Dimensional Security Assessment of an AutoML Training Pipeline“, M.Sc.