Profile
Professor Amr Alanwar is Professor of Cyber-Physical Systems at the Technical University of Munich. His research develops mathematically rigorous methods that enable autonomous, connected and data-driven systems to operate safely while preserving privacy. By combining control theory, formal verification, machine learning and set-based computation, he addresses a central engineering challenge: how to make reliable decisions when system models are incomplete, measurements are noisy and the surrounding environment is uncertain.
Research journey
His early research experience included work as a research assistant at the University of California, Los Angeles, where he contributed to networked and embedded systems research. He later completed his PhD in Computer Science in 2020 within the Cyber-Physical Systems Group at the Technical University of Munich. His doctoral work established a strong foundation in secure state estimation, privacy-preserving computation and techniques for analysing the reachable behaviour of complex systems.
After the doctorate, he joined KTH Royal Institute of Technology in Sweden as a postdoctoral researcher. There, his research advanced data-driven reachability analysis, set-based estimation and predictive control. These methods use observed data to construct guaranteed bounds on future system behaviour, allowing engineers to reason about safety even when a complete mathematical model is unavailable. The work has applications in robotics, automated vehicles, networked control and other safety-critical systems.
Research contribution and impact
Professor Alanwar subsequently served as an Assistant Professor at Constructor University Bremen before joining TUM in September 2023. At TUM Campus Heilbronn, he leads the Professorship of Cyber-Physical Systems. His group studies safety guarantees for learning-enabled systems, formal verification, resilient estimation, secure control and privacy. He has also developed logical zonotopes and related set representations for efficiently analysing systems that combine continuous dynamics with discrete or logical decisions.
A defining feature of his work is the integration of learning with guarantees. His research applies reachability analysis to safe reinforcement learning, autonomous navigation and intelligent transportation; develops privacy-preserving estimation using encryption and differential privacy; and strengthens systems against sensor attacks and uncertainty. His selection for the German Research Foundation’s Emmy Noether Programme in 2025 recognises this independent research direction and supports further work on dependable cyber-physical systems.
Areas of expertise
- Cyber-physical systems
- Reachability analysis
- Safe learning and control
- Privacy-preserving estimation
- Formal verification
- Autonomous and resilient systems
In the network
With more than 120 research publications and a Google Scholar h-index of 19, Professor Alanwar has built a substantial record across control, robotics, privacy and safety-critical computing. His research consistently connects theoretical guarantees with practical problems, providing tools that help intelligent systems learn from data without sacrificing safety, security or confidentiality.
Bibliometric values change over time; figures verified September 2026 from Google Scholar.
