Michael J. BlackAdjunct Professor (Research)
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|CSCI1430||Introduction to Computer Vision|
|CSCI2950-O||Topics in Brain-Computer Interfaces|
|CSCI2950-Q||Topics in Computer Vision|
Research InterestsMy 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.