David J. Fleet

David Fleet is Research Director with Google DeepMind (in Toronto), Professor of Computer Science at the University of Toronto, and Faculty Member of the Vector Institute. He received the PhD in Computer Science from the University of Toronto in 1991. From 1991 to 2000 he was on faculty at Queen's University, Canada, in the Department of Computing and Information Science, with cross-appointments in Psychology and Electrical Engineering. In 1999 he joined the Palo Alto Research Center (PARC) where he managed the Digital Video Analysis Group and the Perceptual Document Analysis Group. He returned to the University of Toronto in October 2003. He served as Chair of the Department of Computer and Mathematical Sciences, University of Toronto Scarborough from 2012 to 2017. He joined Google in 2020. In broad terms, his research interests span computer vision, image processing, visual perception, visual neuroscience, machine learning and computational biology.

In 1996 Dr. Fleet was awarded an Alfred P. Sloan Research Fellowship for his research on biological vision. His 1999 paper with Michael Black on probabilistic detection and tracking of motion boundaries received Honorable Mention for the Marr Prize at the IEEE International Conference on Computer Vision (ICCV). His 2001 paper with Allan Jepson and Thomas El-Maraghi on robust appearance models for visual tracking was awarded runner-up best paper at the IEEE Conference on Computer Vision and Pattern Recognition (CVPR). In 2003, his paper with Eric Saund, James Mahoney and Dan Larner won the best paper award at ACM UIST '03. With Francisco Estrada and Allan Jepson, he won the best paper award at the British Machine Vision Conference (BMVC) in 2009. In 2010, with Michael Black and Hedvig Sidenbladh, he received the Koenderink Prize for fundamental contributions to computer vision that withstood the test of time. His 2021 paper on 3D Variability was named Paper of the Year in 2022 by the Journal Structural Biology. His 2022 paper on the Imagen text to image diffusion model received a best paper award from NeurIPS. He has received Lifetime Acheivement Awards from CIPPRS (2019) and from CS-CAN (2023). He has served as Area Chair for numerous major computer vision and machine learning conferences. He was Associate Editor of IEEE Transactions on Pattern Analysis and Machine Intelligence (2000-2004), Program Co-Chair for the IEEE Conference on Computer Vision and Pattern Recognition in 2003, Associate Editor-In-Chief for IEEE Transactions on Pattern Analysis and Machine Intelligence (2005-2008), Program Co-Chair of ECCV 2014, and Senior Fellow of the Canadian Institute of Advanced Research (2005-2019). He currently serves on the Advisory Board for IEEE PAMI.