Kristen Grauman is an Associate Professor in the Department of
Computer Science at the University of Texas at Austin. Her
research in computer vision and machine learning focuses on visual
search and object recognition. Before joining UT-Austin in
2007, she received her Ph.D. in the EECS department at MIT, in the
Computer Science and Artificial Intelligence Laboratory. She
is an Alfred P. Sloan Research Fellow and Microsoft Research New
Faculty Fellow, a recipient of NSF CAREER and ONR Young Investigator
awards, the Regents' Outstanding Teaching Award from the University
of Texas System in 2012, the PAMI Young Researcher Award in 2013,
the 2013 Computers and Thought Award from the International Joint
Conference on Artificial Intelligence, and a Presidential Early
Career Award for Scientists and Engineers (PECASE) in 2013.
She and her collaborators were recognized with the CVPR Best Student
Paper Award in 2008 for their work on hashing algorithms for
large-scale image retrieval, and the Marr Best Paper Prize at ICCV
in 2011 for their work on modeling relative visual attributes.
She serves on the Editorial Board for the International Journal of
(IJCV), as an Associate Editor in Chief for the
Transactions on Pattern Analysis and Machine Intelligence (TPAMI),
and as a Program Chair of CVPR 2015 in Boston.