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Michael J. Black Adjunct Professor of Computer Science

Michael 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 in 1992. He has been a visiting
researcher at the NASA Ames Research Center and an Assistant Professor
in the Department of Computer Science at the University of Toronto. In
1993 Prof. Black joined the Xerox Palo Alto Research Center where he
managed the Image Understanding area and later founded the Digital
Video Analysis group. In 2000, Prof. Black joined the faculty of
Brown University where he is a Professor of Computer Science. At
CVPR'91 he received the IEEE Computer Society Outstanding Paper Award
for his work with P. Anandan on robust optical flow estimation. His
work also received Honorable Mention for the Marr Prize in 1999 (with
David Fleet) and 2005 (with Stefan Roth). Prof. Black's research
interests in machine vision include optical flow estimation, human
motion analysis and probabilistic models of the visual world. In
computational neuroscience his work focuses on probabilistic models of
the neural code, the neural control of movement and the development
of neural prostheses that directly connect brains and machines to
restore lost function to the physically disabled.

Brown Affiliations

Research Areas

research overview

Michael Black's research addresses estimation and understanding of human movement. His group has been developing computational and mathematical models of movement that can be recovered from video sequences using new computer vision algorithms. At the core of this work are probabilistic models of the visual world that are learned from natural scenes. Furthermore, his group exploits these models of human movement in the design of neural motor prosetheses. In particular they model the relationship between neural firing activity of populations of motor cortical neurons and complex natural movement. The goal is to enable paralyzed patients to control dexterous robot hands using neural signals recorded with an implanted electrode array.

research statement

My research lies at the intersection of computer science and the physical world in which machines must interact with, and adapt to, a complex, dynamic, and partially observable environment. My work focuses on the development of mathematical and computational methods that enable computers to make reliable inferences in the face of uncertain and ambiguous measurements that change over time. I explore these general issues in the context of two seemingly different but, in fact, related problems: the estimation and interpretation of visual motion in image sequences and the decoding of neural signals from the brain.


My computer vision research focuses on:

* the statistics of natural images and image motion;

* articulated human motion estimation and full body tracking;

* the representation and detection of motion discontinuities;

* the estimation of optical flow and the recognition of motion events;

* high-dimensional robust learning and inference.



My research on neural engineering, computational neuroscience, and brain-machine interfaces focuses on:

* statistical models of neural coding;

* probabilistic methods for neural decoding;

* developing neural prostheses using implanted microelectrode arrays;

* bionic systems that directly couple brains and robots.




funded research

U.S. - Uruguay Workshop: Vision in Brains and Machines (PI), NSF, $59,983, 9/15/06-8/31/07

Planning Workshop: Corpora for Computational Neuroscience (PI), NSF, $21,320, 6/2006-5/2007

Neural Interfaces to Enhance Human Motor Performance: Instrumentation for modeling dexterous manipulation (PI), Office of Naval Research, $314,880, 7/1/2006

Research Gift - Honda Research (PI), Honda Research, 25000, 3/1/2006-3/31/2006

Neural Interfaces to Understand Human Motor Performance (Co-PI), Office of Naval Research, $963,000, 10/25/2005-10/26/2006

Statistical Models of the Primate Neocortex: Implementation and Application (Co-PI), National Science Foundation, $479,999, 11/15/2005 - 10/31/2008

Learning Rich Statistical Models of the Visual World for Robust Perception (PI), National Science Foundation, $268,597, 8/1/2005-7/29/2008

Learning Probabilistic Models for Image Motion Analysis (PI), Intel Corporation, $178,669, 11/2004 - 12/2007

Neural Interfaces to Enhance Human Motor Performance (Co-PI), Office of Naval Research, $960,000, 10/4/2004-12/30/2005

Rebuilding, Regnerating and Restoring Function after Traumatic Limb Loss (subcontract) (Co-PI), Veteran's Administration, $146,776, 8/1/2004-7/31/2009

CRCNS: Learning the Neural Code for Prosthetic Control (PI), National Institutes of Health (NIH)-National Institute of Neurological Disorders and Stroke (NINDS), $1,116,350, 8/1/2004-7/30/2007

NEURBOTICS- The Fusion of Neuroscience and Robotics (PI), European Commission, Beyond Robotics Program, Euro 100,000 out of Euro 5,640,048, 1/1/2004 - 1/1/2008

Research Gift - Siemens Corporate Research (PI), Siemens Corporate Research, 50000, 1/1/2003-4/1/2004

The Computer Science of Biologically Embdedded Systems (PI), National Science Foundation, $446,969, 9/2001 - 8/2005

Motion Capture for Statistical Learning of Human Appearance and Motion (PI), Office of Naval Research, $339,340, 5/1/2001 - 5/1/2004

Research Gift - Xerox Foundation (PI), Xerox Foundation, University Affairs Committee Grant, 30000, 11/01/1999-5/31/2000