People

Angela Schoellig is an Alexander von Humboldt Professor for Robotics and Artificial Intelligence at the Technical University of Munich, an Associate Professor at the University of Toronto Institute for Aerospace Studies, and a Faculty Member of the Vector Institute for Artificial Intelligence. Her research combines robotics, control, and machine learning to improve robot performance, safety, and autonomy.

She previously held a Canada Research Chair (Tier 2) in Machine Learning for Robotics and Control and a Canada CIFAR Chair in Artificial Intelligence. Angela has received major recognitions including the Robotics: Science and Systems Early Career Spotlight Award (2019), a Sloan Research Fellowship (2017), and inclusion in MIT Technology Review’s Innovators Under 35 (2017). Her team is also a four-time champion of the North-American SAE AutoDrive Challenge (2018-21).

SiQi Zhou is an Assistant Professor in the School of Computing Science at Simon Fraser University. Her research focuses on developing principled approaches that integrate control theory and machine learning for safe and intelligent robot operation in human-centric environments. More recently, her work has centred on methods that tightly couple perception, reasoning, and action to achieve semantically safe behaviours; see her project page and semanticcontrol.com for further details.

SiQi obtained her PhD and BASc in Engineering Science from the University of Toronto in 2022 and 2016, respectively. Before joining Simon Fraser University, she was a Senior Scientist in the Learning Systems and Robotics Lab at the Technical University of Munich and a postdoc of the Vector Institute for Artificial Intelligence. SiQi has been recognized as an MIT Rising Star in Aerospace in 2021 and an RSS Pioneer in 2022, and was awarded the EU Marie Skłodowska-Curie Actions Fellowship in 2024.

Lukas Brunke is a PhD candidate at the University of Toronto and a researcher at the Technical University of Munich and the Vector Institute for Artificial Intelligence working at the Learning Systems and Robotics Lab supervised by Prof. Angela Schoellig. His research focuses on safe decision-making in robotics, developing theoretical advances in safety-critical control and perception-based methods that leverage semantic understanding to ensure safe robot behaviour.

Martin Schuck is a PhD candidate at the Learning Systems and Robotics (LSY) lab under Prof. Angela Schoellig at the Technical University of Munich. His research interests focus on training reinforcement learning agents for real-world deployment and range from performant high-fidelity simulations to fundamental research on representation learning to solving complex real-world manipulation tasks. He is also actively involved in several scientific open-source projects.

Ralf Römer is a PhD candidate at the Learning Systems and Robotics at the Technical University of Munich, advised by Prof. Angela Schoellig. His research is on embodied AI, i.e., developing intelligent robots that can learn to safely perform complex tasks in the real world under changing and uncertain operating conditions. For this, Ralf is working on diffusion policies and vision-language-action models (VLAs), with a focus on uncertainty quantification, continual learning, and constraint satisfaction.

Oliver Hausdörfer is a PhD candidate at the Learning Systems and Robotics at the Technical University of Munich, advised by Prof. Angela Schoellig. His research regards various robot platforms, including quadrupedal locomotion and robotic manipulation. He is interested in teaching robots complex tasks, from navigating rough environments to dexterous manipulation. For this, he researches methods required for robot learning, including imitation learning, reinforcement learning, and simulations.

Adam Hall is a PhD candidate at the University of Toronto Institute for Aerospace Studies under Prof. Angela Schoellig. His research explores how to combine machine learning with control theory to help robots safely improve their performance over time. Specifically, his research focuses on using differential flatness to improve the efficiency of learning-based control algorithms.

Haocheng Zhao is an incoming PhD researcher at the Learning Systems and Robotics Lab at the Technical University of Munich, advised by Prof. Angela Schoellig. His research focuses on safety-critical control for robotic systems, with an emphasis on geometric representations and semantic-based perception methods for reliable decision-making. His work aims to enable robust robot autonomy in complex and unstructured environments.

Luca Worbis is a Master student in Electrical Engineering and Information Technology at the Technical University of Munich, focusing on robotics, AI, and control.

Feng-En Yeh is a second year Master student in Mechatronics, Robotics and Biomechanics Engineering at TUM and a research student at the Learning Systems and Robotics Lab. His research interests are reinforcement learning and robotic control for real-world deployment.