Marc Deisenroth Team
Quick Info
Research Interests
Machine Learning, Robotics, Control, Signal Processing.
More Information
Curriculum Vitae Publications Google Citations DBLP
Contact Information
Mail: TU Darmstadt, Hochschulstr. 10, 64289 Darmstadt
Office: Room E323, Robert-Piloty-Gebäude S2|02
+49-6151-16-7396
+49-6151-16-7374
marc@ias.tu-darmstadt.de
Marc Deisenroth
Marc joined the IAS in December 2011 as a Senior Research Scientist & Group Leader (Learning for Control).
From February 2010 to December 2011, Marc has been a full-time Research Associate in Dieter Fox' lab at the University of Washington (Seattle). Marc completed his Ph.D. at the Karlsruhe Institute for Technology (Germany) with Uwe D. Hanebeck. Marc conducted his Ph.D. research under Carl Edward Rasmussen's supervision at the Max Planck Institute for Biological Cybernetics (2006–2007) and at the University of Cambridge (2007–2009).
Marc's research interests center around methodologies from modern Bayesian machine learning and their application to control and autonomous robotic systems. Marc's goal is to make robotic and control systems more autonomous by modeling and accounting for uncertainty in a principled way. Potential applications include intelligent prostheses, autonomous robots, and healthcare assistants.
News
- Peter Englert got his research results on model-based imitation learning accepted at the Adaptive Behavior journal.
- Roberto Calandra successfully applied Bayesian optimization to learning gait parameters for biped locomotion. Have a look at the videos!
- Peter Englert got some really good results for imitation learning based on probabilistic trajectory matching. Check out our ICRA paper!
- Zhikun Wang applied fast online Bayesian inference to an intention inference problem in the context of robot table tennis. Check out our IJRR paper!
- RSS 2013: I am the Robotics: Science & Systems 2013 workshop chair.
- EWRL 2012: I am program chair of the 10th European Workshop on Reinforcement Learning (EWRL 2012).
- Check out our YouTube channel on autonomous learning.
Research Interests
- Machine Learning: Gaussian processes, Reinforcement learning, Bayesian inference, Graphical models, Active learning/optimal design, Bayesian optimization
- Control and Robotics: Optimal control, Learning legged locomotion, Robot learning, Imitation learning
- Signal Processing: Bayesian state estimation, System identification, Inference and learning in nonlinear dynamical systems
An full list of publications can be found here.
Marc Deisenroth can be found on [Google Citations].
Citations of Marc Deisenroth
| All | Since 2008 | |
| Citations | 299 | 291 |
| h-index | 9 | 9 |
| i10-index | 8 | 8 |
Key References
- Deisenroth, M.P.; Turner, R.; Huber, M.; Hanebeck, U.D.; Rasmussen, C.E (2012). Robust Filtering and Smoothing with Gaussian Processes, IEEE Transactions on Automatic Control. See Details Download Article BibTeX Reference
- Deisenroth, M.P.; Rasmussen, C.E.; Peters, J. (2009). Gaussian Process Dynamic Programming, Neurocomputing, 72, pp.1508-1524. See Details Download Article BibTeX Reference This paper is among the most cited Neurocomputing articles
- Deisenroth, M.P.; Rasmussen, C.E. (2011). PILCO: A Model-Based and Data-Efficient Approach to Policy Search, International Conference on Machine Learning (ICML 2011). See Details Download Article BibTeX Reference
- Deisenroth, M.P.; Fox, D.; Rasmussen, C.E. (2011). Learning to Control a Low-Cost Robotic Manipulator Using Data-Efficient Reinforcement Learning, Robotics: Science & Systems (RSS 2011). See Details Download Article BibTeX Reference
- Deisenroth, M.P.; Mohamed, S. (2012). Expectation Propagation in Gaussian Process Dynamical Systems, Advances in Neural Information Processing Systems 26 (NIPS), Cambridge, MA: MIT Press., The MIT Press. See Details Download Article BibTeX Reference
- Deisenroth, M.P.; Ohlsson, H. (2011). A General Perspective on Gaussian Filtering and Smoothing: Explaining Current and Deriving new Algorithms, American Control Conference (ACC 2011). See Details Download Article BibTeX Reference
- Deisenroth, M.P.; Calandra, R.; Seyfarth, A.; Peters, J. (2012). Toward Fast Policy Search for Learning Legged Locomotion, Proceedings of the International Conference on Robot Systems (IROS). See Details Download Article BibTeX Reference
Student Supervisions at TU Darmstadt
Current
- Roberto Calandra (Ph.D. student)
- Nooshin HajiGhasemi (M.Sc. Student)
- Felix Schmitt (M.Sc. Student)
- Sanket Kamthe (M.Sc. Student)
- Brian Pfretzschner (B.Sc. Student)
Previous
- Peter Englert (M.Sc., will be starting a Ph.D. at the University of Stuttgart): Model-based Imitation Learning by Probabilistic Trajectory Matching (February 2013)
- Nakul Gopalan (M.Sc., will be starting a Ph.D. at Brown University): Feedback Error Learning for Gait Acquisition (November 2012)
