Björn Ommer

Björn Ommer

Prof. Dr. Björn Ommer is a full professor at LMU where he heads the Computer Vision & Learning Group (previously Computer Vision Group Heidelberg). Before he was a full professor at the Department of Mathematics and Computer Science of Heidelberg University and also served as a one of the directors of the Interdisciplinary Center for Scientific Computing (IWR) and of the Heidelberg Collaboratory for Image Processing (HCI).

He has studied computer science together with physics as a minor subject at the University of Bonn, Germany. After that he pursued his doctoral studies in computer science at ETH Zurich. He received his Ph.D. degree from ETH Zurich for his dissertation “Learning the Compositional Nature of Objects for Visual Recognition” which was awarded the ETH Medal. Thereafter, Björn held a post-doc position in the Computer Vision Group of Jitendra Malik at UC Berkeley.

He serves in the Bavarian AI Council, as an associate editor for the journal IEEE T-PAMI, and previously for Pattern Recognition Letters. Björn is an ELLIS Fellow, an ELLIS unit faculty of the ELLIS unit Munich, affiliated with the Helmholtz foundation, and a PI of the Munich Center for Machine Learning (MCML). He has served as program chair for GCPR, as Senior Area Chair and Area Chair for multiple CVPR, ICCV, ECCV, and NeurIPS conferences, and as workshop and tutorial organizer at these venues. Björn delivered the opening keynote at NeurIPS’23, was awarded the German AI-Prize 2024, the Technology-Prize of Eduard-Rhein-Foundation 2024, and the work leading to Stable Diffusion has been nominated for the German Future Prize of the President of Germany (“Deutscher Zukunftspreis des Bundespräsidenten für Technik und Innovation”).

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  • Organization
    Ludwig Maximilian University of Munich
  • Profession
    Head of Computer Vision & Learning Group
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In personGOAL 13GOAL 11+1
10 July 2025
09:00 - 17:30
EST - New York
CST - Beijing
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AWST - Perth, Australia
In an era where artificial intelligence (AI) is rapidly reshaping...