Kay Hansel

Quick Info

Research Interests

Machine Learning, Robotics, Human-Robot Interaction, Optimal Control, Motor-Skill Learning, Hyper-Autonomous Robot Learning, Musterlösungen

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Contact Information

Kay Hansel
TU Darmstadt, FG IAS,
Hochschulstr. 10, 64289 Darmstadt
Office. Room E225, Building S2|02
work+49-6151-16-20073


Kay Hansel joined the Intelligent Autonomous Systems (IAS) Lab as a Ph.D. student in May 2021. His research interests include machine learning, reinforcement learning, optimal control, and robotics.

Before starting his Ph.D., Kay Hansel completed his Bachelor's degree in Applied Mathematics at the RheinMain University of Applied Sciences and his Master's degree in Autonomous Systems at the TU Darmstadt. His thesis "Probabilistic Dynamic Mode Primitives" was written under the supervision of Svenja Stark and Hany Abdulsamad.




Research Interests

Machine Learning, Reinforcement Learning, Imitation Learning, Optimal Control, Robotics, Telerobotics, Human-Robot Interaction

Key References

Reinforcement Learning

  1. Moos, J.; Hansel, K.; Abdulsamad, H.; Stark, S.; Clever, D.; Peters, J. (2022). Robust Reinforcement Learning: A Review of Foundations and Recent Advances, Machine Learning and Knowledge Extraction, 4, 1, pp.276--315, MDPI.   Download Article [PDF]   BibTeX Reference [BibTex]
  2. Hansel, K.; Moos, J.; Derstroff, C. (2021). Benchmarking the Natural Gradient in Policy Gradient Methods and Evolution Strategies, Reinforcement Learning Algorithms: Analysis and Applications, pp.69--84, Springer.   BibTeX Reference [BibTex]
  3. 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]

Imitation Learning

  1. Hansel, K. (2021). Probabilistic Dynamic Mode Primitives, Master Thesis.   Download Article [PDF]   BibTeX Reference [BibTex]

  

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