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, visual recognition, and action for perception or embodied AI.  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 NSF CAREER and ONR Young Investigator awards, the PAMI Young Researcher Award in 2013, 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) in 2013.  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.