Michael Lutter Contact: mail(at)mlutter.eu Twitter: _mlutter Research Interests: Model-Based Reinforcement Learning, Interpretable and Plausible Models, High-Speed Robot Control, Dexterous Manipulation, Robust Control

Bio: Michael Lutter completed his Ph.D. supervised by Jan Peters at the Institute for Intelligent Autonomous Systems (IAS) TU Darmstadt in November 2021. During his Ph.D., he researched inductive biases for robot learning. Michael also worked with ABB Corporate Research on a joint research project to evaluate the application of robot learning to industrial applications. He completed a research internship at DeepMind, NVIDIA Research and received multiple awards for his research including the AI newcomer award (2019) of the German computer science foundation and was NVIDIA graduate fellowship finalist (2019).

Prior to this Michael held a researcher position at the Technical University of Munich (TUM) for bio-inspired learning for robotics. During this time he worked for the Neurorobotics subproject of the Human Brain Project, a European H2020 FET flagship project. In addition, he taught the classes "Deep Learning for Autonomous Systems” and “Fundamentals of Computer Science for Neuroengineering” within the Elite Master Programm Neuroengineering and participated in teaching Think. Make. Start., a two-week prototyping course. His educational background covers a Bachelors in Engineering Management from University of Duisburg Essen and a Masters in Electrical Engineering from the Technical University of Munich. During his undergraduate studies he also spent one semester at the Massachusetts Institute of Technology studying electrical engineering and computer science. In addition to his studies, Michael worked for ThyssenKrupp, Siemens and General Electric and received multiple scholarships for academic excellence.

News

• (19.Nov 21) - Defended my Ph.D. on Robot Learning [Thesis]
• (29.Sep 21) - New pre-print on learning dynamics models for MPC [Arxiv]
• (10.May 21) - Accepted RSS Paper Robust Value Iteration for Continuous Control [Arxiv]
• (08.May 21) - Accepted ICML Paper Value Iteration in continuous space and time [Arxiv]
• (01.Apr 21) - Accepted ICRA Paper Model-Learning for offline RL [Arxiv]
• (14.Jan 21) - Started my Research Internship with the DeepMind Robotics Team
• (11.Dec 20) - Organizing NeurIPS WS on Inductive Biases and Physically Structured Learning
• (25.Oct 20) - Invited Talk IROS WS on Trends and Advances in ML and Automated Reasoning
• (14.Oct 20) - Robot Juggling paper accepted at CoRL 2020 [Arxiv]
• (01.Oct 20) - My Homepage is finally live :)