Kristen Grauman is a Professor in the Department of Computer Science at the University of Texas at Austin and a Research Director in Facebook AI Research (FAIR). Her research in computer vision and machine learning focuses on video, visual recognition, and action for perception or embodied AI. Before joining UT-Austin in 2007, she received her Ph.D. at MIT and BA at Boston College. She is an IEEE Fellow, AAAI Fellow, Sloan Fellow, a Microsoft Research New Faculty Fellow, and a recipient of 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), the Presidential Early Career Award for Scientists and Engineers (PECASE), the J.K. Aggarwal Prize, and a finalist for the Blavatnik National Award for Young Scientists. 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 has given plenary keynotes at ICLR, IROS, MICCAI, ICPR, BMVC, ICIP, AAAI, IJCAI, and AAMAS. 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) 2015, Neural Information Processing Systems (NeurIPS) 2018, and the IEEE International Conference on Computer Vision (ICCV) 2023.
2023 Edward J. McCluskey Technical Achievement Award
“For contributions to object recognition, unsupervised domain adaptation and visual search.”
Learn more about the Edward J. McCluskey Technical Achievement Award