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Prof. Dr. Wojciech Samek


Fraunhofer Heinrich Hertz Institute
Department of Artificial Intelligence

Einsteinufer 37, D-10587 Berlin

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Prof. Dr. Wojciech Samek

Prof. Dr. Wojciech Samek


Fellow | BIFOLD

Professor | Technische Universität Berlin

Head of AI Department | Fraunhofer HHI

Wojciech Samek is a professor in the department of Electrical Engineering and Computer Science at the Technical University of Berlin and is jointly heading the department of Artificial Intelligence and the Explainable AI Group at Fraunhofer Heinrich Hertz Institute (HHI), Berlin, Germany. He studied computer science at Humboldt University of Berlin from 2004 to 2010, was visiting researcher at NASA Ames Research Center, CA, USA, and received the Ph.D. degree in machine learning from the Technische Universität Berlin in 2014. He is associated faculty at the ELLIS Unit Berlin and the DFG Graduate School BIOQIC, and member of the scientific advisory board of IDEAS NCBR. Furthermore, he is a senior editor of IEEE TNNLS, an editorial board member of Pattern Recognition, and an elected member of the IEEE MLSP Technical Committee. He is recipient of multiple best paper awards, including the 2020 Pattern Recognition Best Paper Award, and part of the expert group developing the ISO/IEC MPEG-17 NNC standard. He is the leading editor of the Springer book “Explainable AI: Interpreting, Explaining and Visualizing Deep Learning” and organizer of various special sessions, workshops and tutorials on topics such as explainable AI, neural network compression, and federated learning. He has co-authored more than 150 peer-reviewed journal and conference papers; some of them listed by Thomson Reuters as “Highly Cited Papers” (i.e., top 1%) in the field of Engineering.

2021 2020 Pattern Recognition Best Paper Award
2019 Best Paper Award at ICML Workshop on On-Device Machine Learning & Compact Deep Neural Network Representations
2019 Honorable Mention Award at IEEE AIVR
2016 Best Paper Award at ICML Workshop on Visualization for Deep Learning
2010 Scholarship of the DFG Research Training Group GRK 1589/1
2006 Scholarship of the German National Merit Foundation (“Studienstiftung des deutschen Volkes”)

  • Deep Learning
  • Interpretable Machine Learning
  • Model Compression
  • Computer Vision
  • Distributed Learning