About me
I am a PhD student at the Technical University of Munich (TUM) in the Learning Systems and Robotics Lab (LSY), advised by Prof. Angela Schoellig. My research aims to contribute towards embodied AI, i.e., intelligent robots that can safely perform complex real-world tasks under changing and uncertain operating conditions. Specifically, I work on generative policies (diffusion models, flow matching, transformers) for imitation learning and offline RL, with a focus on constraint satisfaction, out-of-distribution (OOD) detection and continual learning. I am also excited about generalist robot policies (robot foundation models).
Before joining LSY, I obtained a Master’s degree in Electrical and Computer Engineering at TUM in 2023 and a Bachelor’s degree in Mechatronics at FAU Erlangen-Nuremberg in 2020, funded by the German Academic Scholarship Foundation. During my studies, I spent a semester at EPFL and conducted research in machine learning for robotic throwing with Prof. Aude Billard. Previously, I also worked with Prof. Sandra Hirche at TUM and with Prof. Knut Graichen at FAU. –> In 2021, I did a research internship in optimal control for autonomous driving at Bosch Research in Renningen, Germany.
Student Supervision: I am always open to supervising excellent and ambitious Master and Bachelor students for a semester project or thesis. You can find a non-exhaustive list of potential topics here. If you want to work with me, please send me an email describing your area of interest and attach your CV and up-to-date transcripts.
News
| 03/25 | Our paper “Semantically Safe Robot Manipulation: From Semantic Scene Understanding to Motion Safeguards” has been accepted for the Robotics and Automation Letters (RA-L). Check out the paper here! |
| 02/25 | Our paper “Diffusion Predictive Control with Constraints” has been accepted at the Learning for Dynamics & Control Conference (L4DC). Check out the paper here! |
| 01/25 | Our paper “Flying through Moving Gates without Full State Estimation” has been accepted at the IEEE International Conference on Robotics and Automation (ICRA). You can find the paper here! |
| 09/24 | We are organizing a workshop “Mastering Robot Manipulation in a World of Abundant Data” on November 9 at the Conference on Robot Learning (CoRL) 2024 in Munich. Check out the details here! |
| 07/24 | I have presented our paper “Is Data All That Matters? The Role of Control Frequency for Learning-Based Sampled-Data Control of Uncertain Systems” at the American Control Conference (ACC) in Toronto, Canada. Check out the video here! |
| 05/24 | I have presented our RA-L paper and a workshop paper “Safe Offline Reinforcement Learning using Trajectory-level Diffusion Models” at the International Conference on Robotics and Automation (ICRA) in Yokohama, Japan. Check out the workshop paper here! |
| 01/24 | Our paper “Is Data All That Matters? The Role of Control Frequency for Learning-Based Sampled-Data Control of Uncertain Systems” has been accepted at the American Control Conference (ACC). You can find the paper here! |
| 12/23 | I have joined the Learning Systems and Robotics Lab at TUM as a PhD student, advised by Prof. Angela Schoellig. |
| 10/23 | Our paper “Vision-Based Uncertainty-Aware Motion Planning Based on Probabilistic Semantic Segmentation” has been published in the Robotics and Automation Letters (RA-L). Check out the paper here! |