Kristen
Grauman is a Professor in the Department of Computer Science
at the University of Texas at Austin. Her research in
computer vision and machine learning focuses on video
understanding and embodied perception. Before joining
UT-Austin in 2007, she received her Ph.D. at MIT. She is
an IEEE Fellow, AAAS Fellow, AAAI Fellow, Sloan Fellow, a
Microsoft Research New Faculty Fellow, and a recipient of the
2025 Huang Prize, NSF CAREER and ONR Young Investigator
awards, the PAMI
Young Researcher Award, the 2013 Computers and Thought Award
from the International Joint Conference on Artificial
Intelligence (IJCAI), and the Presidential Early Career Award
for Scientists and Engineers (PECASE). She was inducted
into the UT Academy of Distinguished Teachers in 2017.
She and her collaborators have been recognized with several
Best Paper awards in computer vision, including a 2011 Marr
Prize and a 2017 Helmholtz Prize (test of time award).
She served for six years as an Associate Editor-in-Chief for
the Transactions on Pattern Analysis and Machine Intelligence
(PAMI) and for ten years as an Editorial Board member for the
International Journal of Computer Vision (IJCV). She also served as a
Program Chair of the IEEE Conference on Computer Vision and
Pattern Recognition (CVPR) in 2015, Neural Information
Processing Systems (NeurIPS) in 2018, and IEEE International
Conference on Computer Vision (ICCV) in 2023.