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Jan Peters

Jan Peters is a full professor (W3) for Intelligent Autonomous Systems at the Computer Science Department of the Technische Universitaet Darmstadt. Until 2021, he was also an adjunct senior research scientist at the Max-Planck Institute for Intelligent Systems, where he heads the interdepartmental Robot Learning Group between the departments of Empirical Inference and Autonomous Motion. 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.

Quick Info

Research Interests

Motor Control & Learning, Robotics, Machine Learning, Biomimetic Systems.

More Information

Curriculum Vitae Short Bio Publications Google Scholar DBLP ORCID LinkedIn Xing

Contact Information

Mail. TU Darmstadt, FB-Informatik, FG-IAS, Hochschulstr. 10, 64289 Darmstadt
Office. Room E314, Robert-Piloty-Gebaeude S2|02
work+49-6151-16-25374
fax+49-6151-16-25375

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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.

Short Bio

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-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

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 companies (Amazon, Facebook, Google, ...) as well as many major AI labs at 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.

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).

Jan Peters rarely ever gets angry but he truly hates "pretend professors" who do not take good care of their students and employees. He is truly saddened to see how many professors do not lead their PhD students to graduate, his knuckles turn white when he thinks about the bastards who only lead a small fraction of their PhD students to graduation and who do not coach their PhD graduates and postdocs to finding their own route to success.

Recent Publications

Belousov, B.; Wibranek, B.; Schneider, J.; Schneider, T.; Chalvatzaki, G.; Peters, J.; Tessmann, O. (2022). Robotic Architectural Assembly with Tactile Skills: Simulation and Optimization, Automation in Construction.   Download Article [PDF]   BibTeX Reference [BibTex]

Muratore, F.; Gienger, M.; Peters, J. (2021). Assessing Transferability from Simulation to Reality for Reinforcement Learning, IEEE Transactions on Pattern Analysis and Machine Intelligence (PAMI), 43, 4, pp.1172-1183, IEEE.   Download Article [PDF]   BibTeX Reference [BibTex]

Tosatto, S.; Akrour, R.; Peters, J. (2021). An Upper Bound of the Bias of Nadaraya-Watson Kernel Regression under Lipschitz Assumptions, Stats, 4, pp.1--17.   Download Article [PDF]   BibTeX Reference [BibTex]

Muratore, F.; Eilers, C.; Gienger, M.; Peters, J. (2021). Data-efficient Domain Randomization with Bayesian Optimization, IEEE Robotics and Automation Letters (RA-L), with Presentation at the IEEE International Conference on Robotics and Automation (ICRA), IEEE.   Download Article [PDF]   BibTeX Reference [BibTex]

Hoefer, S.; Bekris, K.; Handa, A.; Gamboa, J.C.; Golemo, F.; Mozifian, M.; Atkeson, C.G., Fox, D.; Goldberg, K.; Leonard, J.; Liu, C.K.; Peters, J.; Song, S.; Welinder, P.; White, M. (2021). Sim2Real in Robotics and Automation: Applications and Challenges, IEEE Transactions on Automation Science (T-ASE), 18, 2, pp.398-400.   Download Article [PDF]   BibTeX Reference [BibTex]

Belousov, B.; Abdulsamad H.; Klink, P.; Parisi, S.; Peters, J. (2021). Reinforcement Learning Algorithms: Analysis and Applications, Studies in Computational Intelligence, Springer International Publishing.   Download Article [PDF]   BibTeX Reference [BibTex]

Watson, J.; Lin, J. A.; Klink, P.; Peters, J. (2021). Neural Linear Models with Functional Gaussian Process Priors, 3rd Symposium on Advances in Approximate Bayesian Inference (AABI).   BibTeX Reference [BibTex]

Watson, J.; Lin J. A.; Klink, P.; Pajarinen, J.; Peters, J. (2021). Latent Derivative Bayesian Last Layer Networks, Proceedings of the International Conference on Artificial Intelligence and Statistics (AISTATS).   BibTeX Reference [BibTex]

Prasad, V.; Stock-Homburg, R.; Peters, J. (2021). Human-Robot Handshaking: A Review, International Journal of Social Robotics.   Download Article [PDF]   BibTeX Reference [BibTex]

Klink, P.; Abdulsamad, H.; Belousov, B.; D'Eramo, C.; Peters, J.; Pajarinen, J. (2021). A Probabilistic Interpretation of Self-Paced Learning with Applications to Reinforcement Learning, Journal of Machine Learning Research (JMLR).   Download Article [PDF]   BibTeX Reference [BibTex]

Tosatto, S.; Chalvatzaki, G.; Peters, J. (2021). Contextual Latent-Movements Off-Policy Optimization for Robotic Manipulation Skills, Proceedings of the IEEE International Conference on Robotics and Automation (ICRA).   BibTeX Reference [BibTex]

Li, Q.; Chalvatzaki, G.; Peters, J.; Wang, Y. (2021). Directed Acyclic Graph Neural Network for Human Motion Prediction, Proceedings of the IEEE International Conference on Robotics and Automation (ICRA).   BibTeX Reference [BibTex]

Prasad, V.; Stock-Homburg, R.; Peters, J. (2021). Learning Human-like Hand Reaching for Human-Robot Handshaking, Proceedings of the IEEE International Conference on Robotics and Automation (ICRA).   Download Article [PDF]   BibTeX Reference [BibTex]

Lutter, M.; Silberbauer, J.; Watson, J.; Peters, J. (2021). Differentiable Physics Models for Real-world Offline Model-based Reinforcement Learning, Proceedings of the IEEE International Conference on Robotics and Automation (ICRA).   Download Article [PDF]   BibTeX Reference [BibTex]

Morgan, A.; Nandha, D.; Chalvatzaki, G.; D'Eramo, C.; Dollar, A.; Peters, J. (2021). Model Predictive Actor-Critic: Accelerating Robot Skill Acquisition with Deep Reinforcement Learning, Proceedings of the IEEE International Conference on Robotics and Automation (ICRA).   BibTeX Reference [BibTex]

Abdulsamad, H.; Nickl, P.; Klink, P.; Peters, J. (2021). A Variational Infinite Mixture for Probabilistic Inverse Dynamics Learning, Proceedings of the IEEE International Conference on Robotics and Automation (ICRA).   Download Article [PDF]   BibTeX Reference [BibTex]

Dam, T.; D'Eramo, C.; Peters, J.; Pajarinen J. (2021). Convex Regularization in Monte-Carlo Tree Search, Proceedings of the International Conference on Machine Learning (ICML).   Download Article [PDF]   BibTeX Reference [BibTex]

Tanneberg, D.; Ploeger, K.; Rueckert, E.; Peters, J. (2021). SKID RAW: Skill Discovery from Raw Trajectories, IEEE Robotics and Automation Letters (RA-L).   Download Article [PDF]   BibTeX Reference [BibTex]

Lutter, M.; Mannor, S.; Peters, J.; Fox, D.; Garg, A. (2021). Value Iteration in Continuous Actions, States and Time, International Conference on Machine Learning (ICML).   Download Article [PDF]   BibTeX Reference [BibTex]

Lutter, M.; Mannor, S.; Peters, J.; Fox, D.; Garg, A. (2021). Robust Value Iteration for Continuous Control Tasks, Robotics: Science and Systems (RSS).   Download Article [PDF]   BibTeX Reference [BibTex]

Urain, J.; Anqi, L.; Puze, L.; D'eramo, C.; Peters, J. (2021). Composable Energy Policies for Reactive Motion Generation and Reinforcement Learning, Robotics: Science and Systems (RSS).   Download Article [PDF]   BibTeX Reference [BibTex]

Lutter, M.; Clever, D.; Kirsten, R.; Listmann, K.; Peters, J. (2021). Building Skill Learning Systems for Robotics, Proceedings of the IEEE International Conference on Automation Science and Engineering (CASE).   BibTeX Reference [BibTex]

Lampariello, R.; Mishra, H.; Oumer, N.W.; Peters, J. (2021). Robust Motion Prediction of a Free-Tumbling Satellite with On-Ground Experimental Validation, Journal of Guidance, Control, and Dynamics, 44, 10, pp.1777-1793.   Download Article [PDF]   BibTeX Reference [BibTex]

Liu, P.; Tateo D.; Bou-Ammar, H.; Peters, J. (2021). Efficient and Reactive Planning for High Speed Robot Air Hockey, 2021 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS).   Download Article [PDF]   BibTeX Reference [BibTex]

Muratore, F.; Gruner, T.; Wiese, F.; Belousov, B.; Gienger, M.; Peters, J. (2021). Neural Posterior Domain Randomization, Conference on Robot Learning (CoRL).   Download Article [PDF]   BibTeX Reference [BibTex]

Wibranek, B.; Liu, Y.; Funk, N.; Belousov, B.; Peters, J.; Tessmann, O. (2021). Reinforcement Learning for Sequential Assembly of SL-Blocks: Self-Interlocking Combinatorial Design Based on Machine Learning, Proceedings of the 39th eCAADe Conference.   Download Article [PDF]   BibTeX Reference [BibTex]

D`Eramo, C.; Davide, T; Bonarini, A.; Restelli, M.; Peters, J. (2021). MushroomRL: Simplifying Reinforcement Learning Research, Journal of Machine Learning Research (JMLR), 22, 131, pp.1-5.   Download Article [PDF]   BibTeX Reference [BibTex]

Liu, P.; Tateo D.; Bou-Ammar, H.; Peters, J. (2021). Robot Reinforcement Learning on the Constraint Manifold, Conference on Robot Learning.   Download Article [PDF]   BibTeX Reference [BibTex]

Veiga, F. F.; Edin B.B; Peters, J. (2020). Grip Stabilization through Independent Finger Tactile Feedback Control, Sensors (Special Issue on Sensors and Robot Control), 20.   Download Article [PDF]   BibTeX Reference [BibTex]

Vinogradska, J.; Bischoff, B.; Koller, T.; Achterhold, J.; Peters, J. (2020). Numerical Quadrature for Probabilistic Policy Search, IEEE Transactions on Pattern Analysis and Machine Intelligence (PAMI), 42, 1, pp.164-175.   Download Article [PDF]   BibTeX Reference [BibTex]

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

  

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