Chad Jenkins is primarily interested in the development of methods for autonomous control and perception through leveraging human performance from the real world. His work furthers the idea that robot control and computational perception are better learned from human demonstration rather than explicit computer programming.
Prof. Jenkins' work strives to address issues of capturing data from the world that is representative of human performance, using machine learning and data analysis to extract structure from performance data, and utilizing structures learned from performance for building autonomous robot controllers and perception mechanisms.
Professor Jenkins earned his B.S. in Computer Science and Mathematics at Alma College (1996), his M.S. in Computer Science at Georgia Tech (1998), and his PhD in Computer Science at the University of Southern California (2003). His dissertation pertained to methods for the capture, analysis, and modeling of kinematic motion.
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Odest Chadwicke Jenkins @ Brown CS
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