Jan Peters

Jan Peters is a full professor (W3) for Intelligent Autonomous Systems at the Computer Science Department of the Technische Universität Darmstadt and, at the same time, he is the dept head of the research department on Systems AI for Robot Learning (SAIROL) at the German Research Center for Artificial Intelligence (Deutsches Forschungszentrum für Künstliche Intelligenz, DFKI). He is also is a founding research faculty member of The Hessian Center for Artificial Intelligence.

Jan Peters graduated from the University of Hagen in 2000 with a Diplom-Informatiker (German M.Sc. in Computer Science) with a focus on artificial intelligence and from Munich University of Technology (TU Muenchen) in 2001 with a Diplom-Ingenieur Elektrotechnik (German M.Eng. in Electrical Engineering), majoring in automation & control. In 2000-2001, he spent two semesters as visiting student at National University of Singapore. Subsequently, he moved to University of Southern California (USC) where he completed another M.Sc. in Computer Science with a focus on Machine Learning and a M.Sc. in Aerospace and Mechanical Engineering with a major in nonlinear dynamics. During his studies, Jan Peters has been a visiting research student at the Department of Robotics at the German Aerospace Research Center in Germany, at Siemens Advanced Engineering in Singapore and at the Department of Humanoid Robotics and Computational Neuroscience at the Advanced Telecommunication Research (ATR) Center in Japan.

From 2001 to 2007, he was a graduate research assistant at the Computational Learning and Motor Control Lab at the Department of Computer Science at the University of Southern California (USC) in Los Angeles, USA, where Jan has been working with Stefan Schaal, Sethu Vijayakumar (now at U. Edinburgh, UK), and Firdaus Udwadia (Department of Mechanical Engineering). Jan Peters received his Ph.D. in Computer Science from the University of Southern California (USC). Chris Atkeson (Robotics Institute at CMU) and Gaurav Sukhatme also guided him to his thesis. In 2011, Jan Peters' PhD Thesis received the Dick Volz Best 2007 US PhD Thesis Runner Up Award based on thesis quality and thesis impact. Jan remains affiliated with the CLMC Lab as an invited researcher. After graduating from USC, Jan Peters became a full-time Senior Research Scientist and Robot Learning Group Leader in the Empirical Inference Department of Bernhard Schoelkopf at the Max-Planck Institute for Biological Cybernetics in 2007-2011 and at the Max-Planck Institute for Intelligent Systems since 2011. In 2011, Jan Peters joined the Technische Universitaet Damstadt as a full professor (W3) founding the Intelligent Autonomous Systems lab. From 2010 until 2021, he was also an adjunct senior research scientist at the Max-Planck Institute for Intelligent Systems, where he used to head the interdepartmental Robot Learning Group between the departments of Empirical Inference and Autonomous Motion. In 2022, he became the department head of the research department on Systems AI for Robot Learning (SAIROL) at the German Research Center for Artificial Intelligence (Deutsches Forschungszentrum für Künstliche Intelligenz, DFKI)

Studies

Topics. Computer Science (Dipl-Inform, MSc, PhD), Electrical Engineering (Dipl-Ing), Aerospace & Mechanical Engineering (MSc)
Universities. Technische Universität München, National University of Singapore (NUS), FernUni Hagen, University of Southern California (USC)

Research Experience

Deutsches Luft- & Raumfahrtzentrum (1997-2000)
ATR Research Center (2000,2003), Japan
University of Southern California (2001-2007), USA
Max Planck Institute for Biological Cybernetics (2007-2010)
Max Planck Institute for Intelligent Systems (2011-2021)
Deutsches Forschungszentrum für Künstliche Intelligenz (2022-now)
Technische Universität Darmstadt (2011-now)

Notable Awards

Dick Volz Best 2007 US PhD Thesis Runner Up Award
ICINCO 2010 Best Paper Awards and Honors
Robotics:Science & Systems 2012 Early Career Spotlight
IROS Best Cognitive Robotics Paper Award 2012
2013 IEEE Robotics & Automation Early Career Award
INNS Young Investigator Award 2013
ICRA Best Cognitive Robotics Paper Award 2014
ERC Starting Grant 2014
IEEE Brain Initiative Best Paper Award 2016
IEEE Fellow 2019
Amazon Research Award 2022

Jan Peters has received a few awards, most notably, he has received the Dick Volz Best US PhD Thesis Runner Up Award, the Robotics: Science & Systems - Early Career Spotlight, the IEEE Robotics & Automation Society's Early Career Award, and the International Neural Networks Society's Young Investigator Award. Together with Nick Roy (MIT), Russ Tedrake (MIT), Jun Morimoto (ATR), Jan Peters founded the IEEE Robotics and Automation Society's Technical Committee on Robot Learning which won the Most Active Technical Committee Award. Jan Peters and Andrew Y. Ng (Stanford) have edited a Special Issue on Robot Learning in the Autonomous Robots journal. Jan Peters has been an Area Chair at Robotics: Science & Systems (R:SS), at the European Conference on Machine Learning (ECML), at the International Conference on Neural Networks (ICANN), at International Conference on Artificial Intelligence & Statistics (AIStats) and at Advances in Neural Information Processing Systems (NIPS). Jan Peters has been an Associate Editor for the IEEE Transactions on Robotics and Jan Peters is an Action Editor for the Journal of Machine Learning Research (JMLR). He has also been program co-chair at the Conference on Robot Learning and at IEEE-RAS International Conference on Humanoid Robots (Humanoids).

Jan Peters cares deeply about student and postdoc supervision and has been blessed by some of the most outstanding students. His more than twenty-five graduated Ph.D. students and more than a dozen former postdocs have done outstandingly well in terms of quality and quantity of research results, awards (including both winners and runner-ups of Georges Giralt PhD Award for the best Robotics PhD thesis in Europe), publications ... and job offers! His alumni have started professorships at prestigious universities in the USA (Carnegie Mellon University, Rutgers University, University of Utah, University of Texas at Austin, ...), in Asia (Kyushu Tech, RIKEN AIP, University of Tokyo, Chinese Academy of Science) and in Europe (KIT, TU Delft, University of Amsterdam, Aalto University, Lübeck University, Leoben University, Imperial College, University College London, ...) as well as major IT/AI companies (Amazon, Facebook/Meta, Google/Deepmind, Boston Dynamics, ...) as well as many major AI labs at more general companies (Bosch Centre for AI, Honda Research Institute, Porsche Motor Sports Lab, Volkswagen AI Lab). Even his Master's and Bachelor's thesis students have gotten Ph.D. positions offered at many prestigious places including MIT, CMU, UW, UC Berkeley, Brown University, Georgia Tech, Oxford, KTH, Max Planck Institutes, etc. He hopes all current and future students will do equally well. If you need more information on Jan Peters, please see his tabular curriculum vitae, his short bio or his complete list of publications.

Recent Publications

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    Kicki, P.; Liu, P.; Tateo, D.; Bou Ammar, H.; Walas, K.; Skrzypczynski, P.; Peters, J. (2024). Fast Kinodynamic Planning on the Constraint Manifold with Deep Neural Networks, IEEE Transactions on Robotics (T-Ro), and Proceedings of the IEEE International Conference on Robotics and Automation (ICRA), 40, pp.277-297.
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    Bhatt, A.; Palenicek, D.; Belousov, B.; Argus, M.; Amiranashvili, A.; Brox, T.; Peters, J. (2024). CrossQ: Batch Normalization in Deep Reinforcement Learning for Greater Sample Efficiency and Simplicity, International Conference on Learning Representations (ICLR), Spotlight.
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    Derstroff, C.; Brugger, J.; Cerrato, M.; Peters, J.; Kramer, S. (2024). Peer Learning: Learning Complex Policies in Groups from Scratch via Action Recommendations, Proceedings of the National Conference on Artificial Intelligence (AAAI).
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    Vincent, T.; Metelli, A.; Belousov, B.; Peters, J.; Restelli, M.; D'Eramo, C. (2024). Parameterized Projected Bellman Operator, Proceedings of the National Conference on Artificial Intelligence (AAAI).
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    Tiboni, G.; Klink, P.; Peters, J.; Tommasi, T.; D'Eramo, C.; Chalvatzaki, G. (2024). Domain Randomization via Entropy Maximization, International Conference on Learning Representations (ICLR).
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    Goeksu, Y.; Almeida-Correia, A.; Prasad, V.; Kshirsagar, A.; Koert, D.; Peters, J.; Chalvatzaki, G. (2024). Kinematically Constrained Human-like Bimanual Robot-to-Human Handovers, ACM/IEEE International Conference on Human Robot Interaction (HRI), Late Breaking Report.
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    Hendawy, A.; Peters, J.; D'Eramo, C. (2024). Multi-Task Reinforcement Learning with Mixture of Orthogonal Experts, International Conference on Learning Representations (ICLR).
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    Reddi, A.; Toelle, M.; Peters, J.; Chalvatzaki, G.; D'Eramo, C. (2024). Robust Adversarial Reinforcement Learning via Bounded Rationality Curricula, International Conference on Learning Representations (ICLR).
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    Boehm, A.; Schneider, T.; Belousov, B.; Kshirsagar, A.; Lin, L.; Doerschner, K.; Drewing, K.; Rothkopf, C.A.; Peters, J. (2024). What Matters for Active Texture Recognition With Vision-Based Tactile Sensors, Proceedings of the IEEE International Conference on Robotics and Automation (ICRA).
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    Lach, L.; Haschke, R.; Tateo, D.; Peters, J.; Ritter, H.; Sol, J.; Torras, C. (2024). Transferring Tactile-based Continuous Force Control Policies from Simulation to Robot, Proceedings of the IEEE International Conference on Robotics and Automation (ICRA).
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    Spartakov, R.; Kshirsagar, A.; Mühl, D.; Schween, R.; Endres, D.M.; Bremmer, F.; Melzig, C.; Peters, J. (2024). Balancing on the Edge: Review and Computational Framework on the Dynamics of Fear of Falling and Fear of Heights in Postural Control, Proceedings of the Annual Meeting of the Cognitive Science Society (CogSci).
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    Holzmann, P.; Maik Pfefferkorn, M.; Peters, J.; Findeisen, R. (2024). Learning Energy-Efficient Trajectory Planning for Robotic Manipulators using Bayesian Optimization, Proceedings of the European Control Conference (ECC).
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    Buechler, D.; Calandra, R.; Peters, J. (2023). Learning to Control Highly Accelerated Ballistic Movements on Muscular Robots, Robotics and Autonomous Systems, 159, 104230.
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    Toelle, M.; Belousov, B.; Peters, J. (2023). A Unifying Perspective on Language-Based Task Representations for Robot Control, CoRL Workshop on Language and Robot Learning: Language as Grounding.
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    Lutter, M.; Peters, J. (2023). Combining Physics and Deep Learning to learn Continuous-Time Dynamics Models, International Journal of Robotics Research (IJRR), 42, 3.
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    Lutter, M.; Belousov, B.; Mannor, S.; Fox, D.; Garg, A.; Peters, J. (2023). Continuous-Time Fitted Value Iteration for Robust Policies, IEEE Transaction on Pattern Analysis and Machine Intelligence (PAMI).
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    Loeckel, S.; Ju, S.; Schaller, M.; van Vliet, P..; Peters, J. (2023). An Adaptive Human Driver Model for Realistic Race Car Simulations, IEEE Transactions on Systems, Man and Cybernetics: Systems (TSMC), 53, 11, pp.6718-6730.
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    Look, A.; Kandemir, M.; Rakitsch, B.; Peters, J. (2023). A Deterministic Approximation to Neural SDEs, IEEE Transactions on Pattern Analysis and Machine Intelligence (PAMI), 45, 4, pp.4023-4037.
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    Liu, Y.; Belousov, B.; Funk, N.; Chalvatzaki, G.; Peters, J.; Tessman, O. (2023). Auto(mated)nomous Assembly, International Conference on Trends on Construction in the Post-Digital Era, pp.167-181, Springer, Cham.
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    Liu, P.; Zhang, K.; Tateo, D.; Jauhri, S.; Hu, Z.; Peters, J. Chalvatzaki, G. (2023). Safe Reinforcement Learning of Dynamic High-Dimensional Robotic Tasks: Navigation, Manipulation, Interaction, 2023 IEEE International Conference on Robotics and Automation (ICRA), IEEE.
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    Zhu, Y.; Nazirjonov, S.; Jiang, B.; Colan, J.; Aoyama, T.; Hasegawa, Y.; Belousov, B.; Hansel, K.; Peters, J. (2023). Visual Tactile Sensor Based Force Estimation for Position-Force Teleoperation, IEEE International Conference on Cyborg and Bionic Systems (CBS), pp.49-52.
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    Zelch, C.; Peters, J.; von Stryk, C. (2023). Start State Selection for Control Policy Learning from Optimal Trajectories, Proceedings of the IEEE International Conference on Robotics and Automation (ICRA).
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    Urain, J.; Funk, N.; Peters, J.; Chalvatzaki G (2023). SE(3)-DiffusionFields: Learning smooth cost functions for joint grasp and motion optimization through diffusion, International Conference on Robotics and Automation (ICRA).
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    Hansel, K.; Urain, J.; Peters, J.; Chalvatzaki, G. (2023). Hierarchical Policy Blending as Inference for Reactive Robot Control, 2023 IEEE International Conference on Robotics and Automation (ICRA), IEEE.
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    Le, A. T.; Hansel, K.; Peters, J.; Chalvatzaki, G. (2023). Hierarchical Policy Blending As Optimal Transport, 5th Annual Learning for Dynamics & Control Conference (L4DC), PMLR.
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    Luis, C.; Bottero, A.G.; Vinogradska, J.; Berkenkamp, F.; Peters, J. (2023). Model-Based Uncertainty in Value Functions, Proceedings of the International Conference on Artificial Intelligence and Statistics (AISTATS).
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    Al-Hafez, F.; Tateo, D.; Arenz, O.; Zhao, G.; Peters, J. (2023). LS-IQ: Implicit Reward Regularization for Inverse Reinforcement Learning, International Conference on Learning Representations (ICLR).
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    Palenicek, D.; Lutter, M.; Carvalho, J.; Peters, J. (2023). Diminishing Return of Value Expansion Methods in Model-Based Reinforcement Learning, International Conference on Learning Representations (ICLR).
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    Buechler, D.; Guist, S.; Calandra, R.; Berenz, V.; Schoelkopf, B.; Peters, J. (2023). Learning to Play Table Tennis From Scratch using Muscular Robots, Proceedings of the IEEE International Conference on Robotics and Automation (ICRA), IEEE T-TRo Track.
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    Urain, J.; Tateo, D.; Peters, J. (2023). Learning Stable Vector Fields on Lie Groups, Proceedings of the IEEE International Conference on Robotics and Automation (ICRA), IEEE R-AL Track.

Privately, Jan Peters enjoys Adventures, Sailing, and Skiing.