Research Assistant


Foto von Samuel Tesfazgi

M.Sc. Samuel Tesfazgi

Technische Universität München

Lehrstuhl für Informationstechnische Regelung (Prof. Hirche)

Postadresse

Postal:
Barerstr. 21
80333 München

Short biography

  • 12/2019 - present: PhD candidate at Chair of Information-Oriented Control (ITR),
    Technical University of Munich (TUM), Germany.

  • 04/2015 - 10/2019: M.Sc. in Electrical Engineering and Information Technology,
    Karlsruhe Institute of Technology (KIT), Karlsruhe, Germany.
    • Thesis: Deep Decentralized Reinforcement Learning for Cooperative Control

  • 10/2011 - 04/2015: B.Sc. in Electrical Engineering and Information Technology,
    Karlsruhe Institute of Technology (KIT), Karlsruhe, Germany.
    • Thesis: Implementation and Testing of Map Matching Strategies for Indoor Navigation

Research Interests

  • System identification using machine learning
  • Safe learning for control
  • Human behavior and intention estimation
  • Human impedance characteristics in movement

Working Field

  • H2020 project "Rehabilitation based on Hybrid Exoskeleton" [ReHyb]

ReHyb

Patients having suffered accidents or stroke often have to go through extensive rehabilitation to regain motor skills for an independent and self-determined life. In contrast to classical physical therapists, robotic rehabilitation systems are able to tirelessly and precisely apply intense manual labor over long periods of time, while accurately measuring performance and improvements of the patient.

As a Team of researchers at TUM and in collaboration with partners across Europe, for the ReHyb project we are developing the control of an upper-body exoskeleton using shared control strategies relying on model-based descriptions of the robotic system and data-driven system identification of the human. Our goal is to develop a patient-specific, assist-as-needed device for rehabilitation and daily living activities.

Open theses (Bachelor / Master / IP / FP)

  • FP / MA: Neuromechnical modeling for physical Human-Exoskeleton-Interaction [PDF]
  • FP / MA: Learning for control of wrist-hand movements based on Functional Electric Stimulation [PDF]
  • FP: Simulation of physical Human-Exoskeleton-Interaction with soft contacts [PDF]

Please feel free to contact me via e-mail, if any of the topics above interest you.

I'm always looking for motivated students, who are interested in my research. So, if none of the above topics fit your specific interests or you have a proposal of your own, don't hesitate to contact me.

Please include your CV, transcript of records, and your preferred starting date in your e-mail.

Publications

2020

  • Köpf, Florian; Tesfazgi, Samuel; Flad, Michael; Hohmann, Sören: Deep Decentralized Reinforcement Learning for Cooperative Control. IFAC-PapersOnLine, 2020 more… BibTeX