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Michael Black
Perceiving Systems Director
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Michael J. Black received his B.Sc. from the University of British Columbia (1985), his M.S. from Stanford (1989), and his Ph.D. in computer science from Yale University (1992). After research at NASA Ames and post-doctoral research at the University of Toronto, he joined the Xerox Palo Alto Research Center in 1993 where he later managed the Image Understanding Area and founded the Digital Video Analysis group. From 2000 to 2010 he was on the faculty of Brown University in the Department of Computer Science (Assoc. Prof. 2000-2004, Prof. 2004-2010). He is an Honorarprofessor at the University of Tuebingen and a founding director at the Max Planck Institute for Intelligent Systems in Tübingen, Germany, where he leads the Perceiving Systems department and serves as Managing Director. He was a Distinguished Amazon Scholar (VP, 2017-2021).
Black is a member of the German National Academy of Sciences Leopoldina and a foreign member of the Royal Swedish Academy of Sciences. He is a recipient of the PAMI Distinguished Researcher Award and all three major test-of-time awards in the field, including the 2022 and 2010 Koenderink Prize (ECCV), the 2013 Helmholtz Prize (ICCV), and the 2020 Longuet-Higgins Prize (CVPR). His work has won several paper awards including the IEEE Computer Society Outstanding Paper Award (CVPR'91). His work received Honorable Mention for the Marr Prize in 1999 and 2005. His early work on optical flow has been widely used in Hollywood films including for the Academy-Award-winning effects in “What Dreams May Come” and “The Matrix Reloaded.” He has contributed to several influential datasets including the Middlebury Flow dataset, HumanEva, and the Sintel dataset. Black has coauthored over 300 peer-reviewed scientific publications.
He is also active in commercializing scientific results, is an inventor on 10 issued patents, and has advised multiple startups. He uniquely combines computer vision, graphics, and machine learning to create digital humans. In 2013, he co-founded Body Labs Inc., which used computer vision, machine learning, and graphics technology licensed from his lab to commercialize "the body as a digital platform." Body Labs was acquired by Amazon in 2017. Black is a co-founder and Chief Scientist of Meshcapade GmbH, where he is building human-centered foundation models that perceive, understand and generate 3D human behavior.
Michael Black received his B.Sc. from the University of British Columbia (1985), his M.S. from Stanford (1989), and his Ph.D. from Yale University (1992). After post-doctoral research at the University of Toronto, he worked at Xerox PARC as a member of research staff and area manager. From 2000 to 2010 he was on the faculty of Brown University in the Department of Computer Science (Assoc. Prof. 2000-2004, Prof. 2004-2010). He is an Honorarprofessor at the University of Tübingen and one of the founding directors at the Max Planck Institute for Intelligent Systems in Tübingen, Germany, where he leads the Perceiving Systems department and serves as Managing Director. He was also a Distinguished Amazon Scholar (VP, 2017-2021). He is a recipient of the PAMI Distinguished Researcher Award and all three major test-of-time awards in Computer Vision, including the 2022 and 2010 Koenderink Prize, the 2013 Helmholtz Prize, and the 2020 Longuet-Higgins Prize. He is a member of the German National Academy of Sciences Leopoldina and a foreign member of the Royal Swedish Academy of Sciences. In 2013 he co-founded Body Labs Inc., which was acquired by Amazon in 2017. Black is a co-founder and Chief Scientist of Meshcapade GmbH.
Michael Black received a B.Sc. from the University of British Columbia (1985), M.S. from Stanford (1989), and Ph.D. from Yale University (1992). He held positions at the University of Toronto, Xerox PARC, and Brown University. He is an Honorarprofessor at the University of Tübingen and one of the founding directors at the Max Planck Institute for Intelligent Systems in Tübingen, Germany, where he leads the Perceiving Systems department and serves as Managing Director. He was a Distinguished Amazon Scholar (2017-2021). He is a recipient of the PAMI Distinguished Researcher Award, the 2022 and 2010 Koenderink Prize, the 2013 Helmholtz Prize, and the 2020 Longuet-Higgins Prize. He is a member of the German National Academy of Sciences Leopoldina and a foreign member of the Royal Swedish Academy of Sciences. In 2013 he co-founded Body Labs Inc., which was acquired by Amazon in 2017. He is co-founder and Chief Scientist of Meshcapade.
Michael Black received his B.Sc. from the University of British Columbia (1985), M.S. from Stanford (1989), and Ph.D. from Yale (1992). He held positions at the University of Toronto, Xerox PARC, Brown, and Amazon. He is an Honorarprofessor at the University of Tübingen and a founding director at the Max Planck Institute for Intelligent Systems. He is a recipient of the PAMI Distinguished Researcher Award, the 2022 and 2010 Koenderink Prize, the 2013 Helmholtz Prize, and the 2020 Longuet-Higgins Prize. He is a member of two national academies (Germany and Sweden). He has co-founded two companies: Body Labs and Meshcapade.
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Yale University, New Haven, CT Ph.D., Computer Science, 1992.
Stanford University, Stanford, CA M.S., Computer Science, 1989.
The University of British Columbia, Vancouver, BC B.Sc., Honours Computer Science, 1985.
2023 PAMI Distinguished Researcher Award.
2022 Koenderink Prize for Fundamental Contributions in Computer Vision, for the paper "A naturalistic open source movie for optical flow evaluation", by Butler, D. J. and Wulff, J. and Stanley, G. B. and Black, M. J.
Best Paper Award, German Conference on Pattern Recognition, GCPR 2022, for the paper "InvGAN: Invertible GANs", by Partha Ghosh, Dominik Zietlow, Michael J. Black, Larry S. Davis, Xiaochen Hu.
Max-Planck-Gründungspreis des Stifterverbandes, Science Prize 2022 in the Entrepreneurship category, to Naureen Mahmood, Talha Zaman, and Michael J. Black for the Meshcapade GmbH team, in recognition of this successful spin-off and the particularly high impact on society. Berlin, June 21, 2022.
German National Academy of Sciences Leopoldina Member since May 2021.
2020 Longuet-Higgins Prize for the paper Sun, D., Roth, S., Black, M. J., “Secrets of optical flow estimation and their principles,” In IEEE Conf. on Computer Vision and Pattern Recognition (CVPR), pages: 2432–2439, IEEE, June 2010.
Alumni Research Award University of British Columbia, Department of Computer Science, 2018.
Royal Swedish Academy of Sciences Foreign member, Class for Engineering Sciences, since June 2015.
2013 Helmholtz Prize for the paper: Black, M. J., and Anandan, P., "A framework for the robust estimation of optical flow,'' IEEE International Conference on Computer Vision, ICCV, pages 231-236, Berlin, Germany. May 1993.
2010 Koenderink Prize for Fundamental Contributions in Computer Vision, with Sidenbladh, H. and Fleet, D. J. for the paper "Stochastic tracking of 3D human figures using 2D image motion,'' European Conference on Computer Vision, 2000.
Best Paper Award, Eurographics 2017, for the paper "Sparse Inertial Poser: Automatic 3D Human Pose Estimation from Sparse IMUs", by von Marcard, T., Rosenhahn, B., Black, M. J., Pons-Moll, G.
"Dataset Award" at the Eurographics Symposium on Geometry Processing 2016, with F. Bogo, J. Romero, and M. Loper, for the paper "FAUST: Dataset and evaluation for 3D mesh registration," CVPR 2014.
Best Paper Award, International Conference on 3D Vision (3DV), 2015, with A. O. Ulusoy and A. Geiger, for the paper "Towards Probabilistic Volumetric Reconstruction using Ray Potentials."
Best Paper Award, INI-Graphics Net, 2008, First Prize Winner of Category Research, with S. Roth for the paper "Steerable random fields."
Best Paper Award, Fourth International Conference on Articulated Motion and Deformable Objects (AMDO-e 2006), with L. Sigal for the paper "Predicting 3D people from 2D pictures.''
Marr Prize, Honorable Mention, Int. Conf. on Computer Vision, ICCV-2005, Beijing, China, Oct. 2005 with S. Roth for the paper "On the spatial statistics of optical flow.''
Marr Prize, Honorable Mention, Int. Conf. on Computer Vision, ICCV-99, Corfu, Greece, Sept. 1999 with D. J. Fleet for the paper "Probabilistic detection and tracking of motion discontinuities.''
IEEE Computer Society, Outstanding Paper Award, Conference on Computer Vision and Pattern Recognition, Maui, Hawaii, June 1991 with P. Anandan for the paper "Robust dynamic motion estimation over time.''
Commendation and Chief's Award, Henrico County Division of Police, County of Henrico, Virginia, April 19, 2007.
University of Maryland, Invention of the Year, 1995, "Tracking and Recognizing Facial Expressions,'' with Y. Yacoob.
University of Toronto, Computer Science Students' Union Teaching Award for 1992-1993.
Max Planck Institute for Intelligent Systems Tübingen, Germany Director, 1/11 - present Managing Director, 7/23 - present, 2/13 - 6/15, 3/18 - 11/18
Meshcapade Tübingen, Germany Chief Scientist (Dec. 2022-present) and co-founder.
Amazon Tübingen, Germany Distinguished Amazon Scholar (VP Technology - Software Dev), 11/17 - 12/21
Eberhard Karls Universität Tübingen, Faculty of Science, Department of Computer Science Tübingen, Germany Honorarprofessor, 05/22/12 - present
Body Labs Inc. New York, NY, USA Co-founder, Science Advisor, Member of the Board, 01/13 - 10/2017
ETH Zürich, Dept. of Information Technology and Electrical Engineering Zürich, Switzerland Visting Professor, 04/2014 - 04/2016
Stanford University, Electrical Engineering Stanford, CA Visiting Professor, 5/11-4/12, 7/12-7/13
Brown University, Department of Computer Science, Providence, RI Adjunct Professor (Research), 1/11-present Professor, 7/04-12/10 Associate Professor, 7/00-6/04
My research addressed the problem of estimating and explaining motion in image sequences. I developed methods detecting and tracking 2D and 3D human motion including the introduction of particle filtering for 3D human tracking and belief propagation for 3D human pose estimation. I worked on probabilistic models of images include the high-order Field of Experts model. I worked on 3D human shape estimation from images and video and developed applications of this technology. I also developed mathematical models for decoding neural signals. This included the first uses of particle filtering and Kalman filtering for decoding motor cortical neural activity and the first point-and-click cortical neural brain-machine-interface for people with paralysis.
Xerox Palo Alto Research Center, Palo Alto, CA Area Manager, Image Understanding Area, 1/96-7/00 Member of Research Staff, 9/93-12/95
Research included modeling image changes (motion, illumination, specularity, occlusion, etc.) in video as a mixture of causes. I developed methods of motion explanation; that is, the extraction of mid-level or high-level concepts from motion. This included the modeling and recognition of motion "features" (occlusion boundaries, moving bars, etc.), human facial expressions and gestures, and motion "texture" (plants, fire, water, etc.). I applied these methods to problems in video indexing, motion for video annotation, teleconferencing, and gestural user interfaces. Other research included robust learning of image-based models, regularization with transparency, anisotropic diffusion, and the recovery of multiple shapes from transparent textures.
University of Toronto, Toronto, Ontario Assistant Professor, Department of Computer Science, (8/92 - 9/93).
Research included the application of mixture models to optical flow, detection and tracking of surface discontinuities using motion information, and robust surface recovery in dynamic environments.
Yale University, (9/89-8/92) New Haven, CT Research Assistant, Department of Computer Science.
Research in the recovery of optical flow, incremental estimation, temporal continuity, applications of robust statistics to optical flow, the relationship between robust statistics and line processes, the early detection of motion discontinuities, and the role of representation in computer vision.
NASA Ames Research Center, (6/90-8/92) Moffett Field, CA Visiting Researcher, Aerospace Human Factors Research Division.
Developed motion estimation algorithms in the context of an autonomous Mars landing and nap-of-the-earth helicopter flight and studied the psychophysical implications of a temporal continuity assumption.
Advanced Decision Systems, (12/86-6/89) Mountain View, CA Computer Scientist, Image Understanding Group.
Research on spatial reasoning for robotic vehicle route planning and terrain analysis. Vision research including perceptual grouping, object-based translational motion processing, the integration of vision and control for an autonomous vehicle, object modeling using generalized cylinders, and the development of an object-oriented vision environment.
GTE Government Systems, (6/85-12/86) Mountain View, CA Engineer, Artificial Intelligence Group.
Developed expert systems for multi-source data fusion and fault location.
Miscellaneous, ('78-'85)
Summer undergraduate researcher at UBC; park ranger's assistant; volunteer firefighter, busboy; and probably my worst job: cleaning dog kennels.