Michael Schwarz

Michael Schwarz is a postdoctoral researcher at the Technical University of Munich (TUM) in Prof. Helmut Seidl's group within the Department of Informatics, and a member of the DFG Research Training Group ConVeY (Continuous Verification of Cyber-Physical Systems).

His educational background includes:

• B.Sc. in Computer Science from TUM (2016)
• M.Sc. in Computer Science from TUM (2019)
• Dr. rer. nat. (PhD) from TUM (2025, summa cum laude)

His research centers on Static Analysis, specializing in Sound Static Analysis by Abstract Interpretation. Key contributions include developing techniques for efficient abstract interpretation of multi-threaded programs, making static analysis incremental to enhance usability, and designing novel analyses for overlooked C language features. His work primarily utilizes the Goblint framework for multi-threaded C programs, which he co-maintains with researchers from the University of Tartu.

Recent publications (2023-2025) reveal a concentrated focus on advancing concurrency analysis and precision recovery in flow-sensitive contexts, with notable emphasis on thread-modular approaches and context-sensitivity optimizations for C programs. This trajectory has yielded recognition including a VMCAI 2024 Best Paper Award and SV-COMP'25 competition wins.

Award highlights:

• Best Paper Award at VMCAI 2024
• SV-COMP'25 data race category winner (2025)
• Recognition Award from Huawei for Goblint's industrial benchmark performance (2025)

While specific advisee listings aren't provided, Schwarz actively contributes to academic service as PC member for SOAP '25 and NSAD '24, plus reviewer for STTT and CSV conferences. His research is supported by the DFG ConVeY grant focusing on cyber-physical systems verification.

He leads development of the Goblint static analysis framework and participates in the ConVeY research consortium, maintaining active collaborations with the University of Tartu on multi-threaded program analysis.