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Prof. Dr. Thomas Wiegand


Technische Universität Berlin

Einsteinufer 37, D-10587 Berlin

Prof. Dr. Thomas Wiegand


Fellow | BIFOLD

Chair | ITU/WHO Focus Group on “Artificial Intelligence for Health”

Executive Director | Fraunhofer HHI

Professor for Electrical Engineering and Computer Science | Technical University Berlin

Thomas Wiegand is a professor in the department of Electrical Engineering and Computer Science at the Technical University of Berlin and is jointly heading the Fraunhofer Heinrich Hertz Institute, Berlin, Germany. He received the Dipl.-Ing. degree in Electrical Engineering from the Technical University of Hamburg-Harburg, Germany, in 1995 and the Dr.-Ing. degree from the University of Erlangen-Nuremberg, Germany, in 2000.

As a student, he was a Visiting Researcher at Kobe University, Japan, the University of California at Santa Barbara and Stanford University, USA, where he also returned as a visiting professor. He was a consultant to Skyfire, Inc., Mountain View, CA, and is currently a consultant to Vidyo, Inc., Hackensack, NJ, USA.

Since 1995, he has been an active participant in standardization for multimedia with many successful submissions to ITU-T and ISO/IEC. In 2000, he was appointed as the Associated Rapporteur of ITU-T VCEG and from 2005-2009, he was Co-Chair of ISO/IEC MPEG Video.

The projects that he co-chaired for the development of the H.264/MPEG-AVC standard have been recognized by an ATAS Primetime Emmy Engineering Award. He was also a recipient of a ATAS Primetime Emmy Engineering Award for the development of H.265/MPEG-HEVC and a pair of NATAS Technology & Engineering Emmy Awards. For his research in video coding and transmission, he received numerous awards including the Vodafone Innovations Award, the EURASIP Group Technical Achievement Award, the Eduard Rhein Technology Award, the Karl Heinz Beckurts Award, the IEEE Masaru Ibuka Technical Field Award, and the IMTC Leadership Award. He received multiple best paper awards for his publications. Since 2014, Thomson Reuters named him in their list of “The World’s Most Influential Scientific Minds” as one of the most cited researchers in his field. He is a recipient of the ITU150 Award. He has been elected to the German National Acdemy of Engineering (Acatech) and the National Academy of Science (Leopoldina).

Since 2018, he has been appointed the chair of the ITU/WHO Focus Group on Artificial Intelligence for Health.

2018 Member of German National Academy of Sciences (Leopoldina)
2017 Primetime Emmy Engineering Award
2016 Member of National Academy of Science and Engineering (acatech)
2015 ITU150 Award
2013 Research Award for Technical Communication of Alcatel Lucent Foundation
2012 IEEE Masaru Ibuka Consumer Electronics Award—Technical Field Award
2011 IEEE Fellow
2010, 2011 Eduard Rhein Technology / Karl Heinz Beckurts Award
2009 Innovations Award of Vodafone Foundation
2008, 2009 Primetime / Technology & Engineering Emmy Awards

  • Signal processing
  • Data and video compression
  • Communications
  • Human visual system
  • Applied machine learning

Galip Ümit Yolcu, Thomas Wiegand, Wojciech Samek, Sebastian Lapuschkin

DualView: Data Attribution from the Dual Perspective

February 19, 2024

Reduan Achtibat, Maximilian Dreyer, Ilona Eisenbraun, Sebastian Bosse, Thomas Wiegand, Wojciech Samek, Sebastian Lapuschkin

From attribution maps to human-understandable explanations through Concept Relevance Propagation

September 20, 2023

Reduan Achtibat, Maximilian Dreyer, Ilona Eisenbraun, Sebastian Bosse, Thomas Wiegand, Wojciech Samek, Sebastian Lapuschkin

From ‚Where‘ to ‚What‘: Towards Human-Understandable Explanations through Concept Relevance Propagation

June 07, 2022

Explainable AI| Oct 04, 2023

AI - finally explainable to humans

As of today it remains difficult to understand how an AI system reaches its decisions. Scientists at the Fraunhofer Heinrich-Hertz-Institut (HHI) and the Berlin Institute for the Foundations of Learning and Data (BIFOLD) at TU Berlin have collaborated for many years to make AI explainable. In their new paper the researchers present Concept Relevance Propagation (CRP), a new method for explainable AI that can explain individual AI decisions as concepts understandable to humans. 

BIFOLD Update| Aug 06, 2020

An overview of the current state of research in BIFOLD

Since the official announcement of the Berlin Institute for the Foundations of Learning and Data in January 2020, BIFOLD researchers achieved a wide array of advancements in the domains of Machine Learning and Big Data Management as well as in a variety of application areas by developing new Systems and creating impactfull publications. The following summary provides an overview of recent research activities and successes.