Academic Career and Research Areas

Prof. Sami Haddadin is the Executive Director of the Munich Institute of Robotics and Machine Intelligence (MIRMI) at the Technical University of Munich (TUM) and holds the Chair of Robotics and Systems Intelligence. His research interests include robotics, machine learning, non-linear control, and human motor intelligence.

From 2014 to 2018, Sami Haddadin was Full Professor and Director of the Institute of Automatic Control at Gottfried Wilhelm Leibniz Universität Hannover, Germany. Prior to that, he held various positions as a research associate at the German Aerospace Center (DLR). He received degrees in Electrical Engineering, Computer Science, and Technology Management from the Technical University of Munich and the Ludwig-Maximilians-Universität München. He received his doctorate with high distinction from RWTH Aachen. He has published more than 200 scientific articles. He has been honored with numerous prestigious awards and prizes for his scientific work. His patent on “Tactile Robots” is listed as the most recent addition to the “Milestone made in Germany” (DPMA) collection.

Awards

  • IEEE Fellow (2024)
  • Gottfried Wilhelm Leibniz Prize of the German Research Foundation DFG (2019)
  • German President’s Award for Innovation in Science and Technology (2017)
  • Alfried Krupp Award for Young Professors (2015)
  • IEEE/RAS Early Career Award (2015)

Kühn J., Hu T., Pozo Fortunic E. & Jensen E., Haddadin S. (2024): “The synergy complement control approach for seamless limb-driven prostheses”. In: Nature Machine Intelligence 6 (2024), pp. 481–492.

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Díaz Ledezma F., Haddadin S. (2023):  “Machine learning–driven self-discovery of the robot body morphology”. In: Science Robotics 8.85 (2023).

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Haddadin S., De Luca A. & Albu-Schäffer A. (2017): "Robot Collisions: A Survey on Detection, Isolation, and Identification". IEEE Transactions on Robotics, 33(6), 1292-1312.

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Hochberg LR., Bacher D., Jarosiewicz B,. Masse NY., Simeral JD, Vogel J., Haddadin S., Liu J., Cash S., van der Smagt  P. & Donoghue J. (2012): "Reach and grasp by people with tetraplegia using a neurally controlled robotic arm". Nature 485, 372–375.

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Haddadin S., Haddadin S., Khoury A., Rokahr T., Parusel S., Burgkart R., Bicchi A., Albu-Schäffer, A. (2012): "On making robots understand safety: Embedding injury knowledge into control". The International Journal of Robotics Research. 31(13): 1578–1602.

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