Thomas B.

Thomas B. is an experienced AI Research Engineer currently working at Helsing, focusing on reinforcement learning methods for planning problems in the defense industry. Previously, Thomas conducted research on deep reinforcement learning at the Robotic Systems Lab, where the thesis aimed at developing a framework for safe and robust behavior in robotics. At Design AI, Thomas contributed to the reimplementation of DeepMind's AlphaStar architecture, emphasizing efficient strategies for experience collection in deep reinforcement learning. Prior experience includes software engineering roles at Magazino GmbH, improving firmware architecture and integrating systems for robotics applications, as well as designing high-performance vehicle suspension parts during an internship with the TUfast e.V. Racing Team. Thomas holds a Master’s degree in Robotics, Cognition, Intelligence from the Technical University of Munich and has pursued further studies in Deep Learning at ETH Zürich. Academic background also includes a Bachelor's degree in Mechanical Engineering from the Technical University of Munich and studies at Sorbonne Université.