Odest C. Jenkins Associate Professor of Computer Science, Associate Professor of Engineering

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.

Brown Affiliations

Research Areas

research overview

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.

research statement

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 three basic questions. First, how can we capture data from the world that is representative of human performance? Second, how can machine learning and data analysis be used to extract dynamical structure from performance data? Lastly, how can we utilize learned dynamics for building autonomous robot controllers and perception mechanisms?

His previous efforts were mostly geared towards humanoid robotics with respect to learning primitive behaviors for robot control through imitation. More generally, he addresses perception, control, and learning issues at the intersection of robotics, computer vision, computer animation, machine learning and interactive systems.