I am an Assistant Professor at the Department of Computer Science, Vanderbilt University. My research interests include physics-enhanced learning, nonparametric models, and safe learning-based control
I am looking for PhD students and postdocs to join my group: Openings
The modeling and control of modern applications such as autonomous driving or human-robot interaction can be excessively time-consuming or even unfeasible due to the growing complexity of technical systems. To address these challenges, data-driven models are a viable solution that requires minimal expert knowledge and have shown remarkable results. However, a major drawback of these models is their unpredictable outcomes, which limits their applicability to non-safety critical systems.
My research focuses on safe learning-based modeling and control of physical systems. I am working on developing novel data-driven control methods that ensure both safe operation and high-performance for the closed-loop system. In addition, I am exploring algorithms that incorporate physical prior knowledge into learning-based models to enhance their generalizability, reliability and interpretability. My research outcomes contribute to the development of safe, robust, and intelligent control methods for physical systems.
Thomas Beckers is an Assistant Professor of Computer Science and the Institute for Software Integrated Systems at Vanderbilt University. Before joining Vanderbilt, he was a postdoctoral researcher at the Department of Electrical and Systems Engineering, University of Pennsylvania, where he was member of the GRASP Lab, PRECISE Center and ASSET Center. In 2020, he earned his doctorate in Electrical Engineering at the Technical University of Munich (TUM), Germany. He received the B.Sc. and M.Sc. degree in Electrical Engineering in 2010 and 2013, respectively, from the Technical University of Braunschweig, Germany. In 2018, he was a visiting researcher at the University of California, Berkeley. He is a DAAD AInet fellow and was awarded with the Rhode & Schwarz Outstanding Dissertation prize. His research interests include physics-enhanced learning, nonparametric models, and safe learning-based control.
06/2023 I will present our poster on "Physics-enhanced Gaussian Process Variational Autoencoder" at L4DC in Philadelphia
04/2023 If you are interested in Gaussian Process based control, please join our workshop at IFAC WC
03/2023 I will present our most recent work on Gaussian Process Port-Hamilonian Systems at the Artificial Intelligence for Robust Engineering and Science (AIRES) workshop
03/2023 Our paper "Physics-enhanced Gaussian Process Variational Autoencoder" has been accepted at L4DC 2023.
03/2023 Two accepted paper at IFAC WC. In addition, we will organize a workshop on Gaussian process based identification and Control
03/2023 I gave a seminar on Gaussian Process Port-Hamiltonian systems at University of Wuppertal
01/2023 I offer a project at the Vanderbilt School of Engineering Summer Research Program for undergraduates.
01/2023 I've started my new position as Assistant Professor of Computer Science at Vanderbilt University.
12/2022 I presented our three papers on Gaussian process based learning and control at the IEEE Conference on Decision and Control
10/2022 It was my pleasure to give a keynote at the IFAC Symposium on Robot Control, Oct 17-20, 2022
09/2022 We will organize a workshop on Gaussian Process Learning-based Control at the IEEE Conference on Decision and Control (CDC) 2022
07/2022 All of our three papers have been accepted at CDC 2022. See you there!
06/2022 Our article "Safe Trajectory Tracking for Underactuated Vehicles with Partially Unknown Dynamics” has been accepted for publication in the Journal of Geometric Mechanics.
06/2022 I am happy to share that I will be joining the Department of Computer Science at Vanderbilt University as Assistant Professor in January 2023.
05/2022 I gave a seminar at Technical University of Darmstadt, German Aerospace Center (DLR), and Leibniz University Hannover
04/2022 I gave a seminar at Vanderbilt University
02/2022 I gave a seminar at Columbia University
02/2022 I have been selected as a DAAD AInet fellow for the Postdoc-NeT-AI 3/2022 – AI and Robotics