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Professor, Computer Science and Engineering
Faculty-Affiliate, Electrical and Computer Engineering
Director, Center for Visual Computing
Computer Graphics, Computer Vision, Signal Processing, Rendering, Visual computing
Ramamoorthi's research group develops the theoretical foundations, mathematical representations and computational models for the visual appearance of objects, digitally recreating or rendering the complexity of natural appearance. The group's research program cuts across computer graphics, computer vision and signal processing with applications in sparse reconstruction and frequency analysis, interactive photorealistic rendering, acquisition and representation of data-driven appearance, image and video editing, light-field cameras, physics-based vision and lighting-insensitive recognition. This work has led to more than 100 publications, including more than 50 SIGGRAPH or TOG papers, and has been recognized in 2005 by a Sloan Fellowship and an NSF CAREER award, and in 2007 with an ONR Young Investigator Award and the ACM SIGGRAPH Significant New Researcher Award. Subsequently, Ramamoorthi received a Presidential Early Career Award in a White House ceremony in December 2008, and an Okawa Foundation Award in 2011, as well as five Google research awards from 2014-2017. Prof. Ramamoorthi was appointed as the inaugural holder of the Ronald L. Graham Chair of Computer Science in March 2016, and was selected both an IEEE and an ACM Fellow in 2017.
Prior to joining UC San Diego, Ramamoorthi was on the faculty of the Electrical Engineering and Computer Science Department at UC Berkeley from January 2009 to June 2014. Since the fall of 2002 (until December 2008), he was on the faculty of the Columbia Computer Science Department. Before that (1998-2002), he completed his Ph.D. in the Stanford Computer Science Department, working in the Computer Graphics Laboratory with Pat Hanrahan. Earlier (1994-98), he was an undergraduate at the California Institute of Technology, getting a BS with Honor in Engineering and Applied Science, MS in Computer Science and an MS in Physics.
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