
About
Thomas Beckers is an Assistant Professor of Computer Science at Vanderbilt University's School of Engineering, joining in January 2023. He holds a Ph.D. in Electrical Engineering from the Technical University of Munich (2020), and B.Sc./M.Sc. degrees from Technical University of Braunschweig (2010/2013). His research bridges machine learning and control theory to develop safe, robust algorithms for complex systems like autonomous vehicles and soft robotics. He is a DAAD AInet Fellow and recipient of the Rhode & Schwarz Outstanding Dissertation Award.
His work focuses on physics-enhanced learning and safe control strategies, leveraging Bayesian methods and port-Hamiltonian systems. Recent projects include developing uncertainty-aware control frameworks and Python tools like PyGpPHs for modeling physical systems. He advises students Peilun Li and Kaiyuan Tan, and has organized workshops at major conferences such as ACC and CDC. His lab explores topics ranging from PDE system identification to geometric control of aerial robots.
Notable achievements include organizing large-scale workshops (e.g., 2023 CDC workshop with 80+ participants) and securing RAMP awards for data-driven control research. His publications emphasize safety, interpretability, and integration of physical priors into machine learning models.
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