Past Keynote Speakers (CVIS 2019)
Title: How to Build an Applied Research Group in The Financial Services Industry
Abstract: Artificial Intelligence is gaining broad adoption in the financial industry, and with good reason. AI provides the opportunity to create new revenue streams, optimize operations and make better investment decisions. In this talk, I will describe some of the challenges and strategies in creating an AI group with the rare skill set that is required to truly leverage AI in finance. I will also describe some of the most impactful use cases in the industry, and propose a hypothesis of where we may want to be in five years. Yevgeniy Vahlis Head of Artificial Intelligence Technology at BMO Yevgeniy Vahlis is the Head of the Artificial Intelligence Technology group at BMO Financial Group. Prior to joining BMO, Yevgeniy built machine learning research groups at Borealis AI and Georgian Partners and worked closely with startups to introduce applied research into their products. Yevgeniy kicked off his career at AT&T Labs in New York as a research scientist after completing his PhD in Computer Science at the University of Toronto and a year of postdoctoral studies at Columbia University. |
Title: Multi-View 3D Reconstruction of Atomic Resolution Biomolecules
Abstract: Electron Cryo-microscopy (Cryo-EM) is a vision-based technique for estimating the 3D structure of biological molecules at atomic resolutions. It addresses one of the foremost problems in biology, namely macromolecular structure discovery. The problem, in a nutshell, is a form of multi-view 3D structure determination, inferring the 3D electron density of a particle from a large set of 2D images from an electron microscope. I'll outline the nature of the problem and several contributions that have led to a new generation of cryo-EM algorithms that are reshaping structural biology. David J. Fleet Professor, Dept. of Computer Science and Dept. of Computer and Mathematical Sciences, University of Toronto Faculty Member, Vector Institute Associate Research Director, Industry Innovation, Vector Institute Senior Fellow, Canadian Institute for Advanced Research Canada CIFAR Artificial Intelligence Chair David Fleet is 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. 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, his work with Michael Black and Hedvig Sidenbladh on human pose tracking received the Koenderink Prize for fundamental contributions to computer vision that withstood the test of time. 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. His research interests include computer vision, image processing, visual perception, and visual neuroscience. He has published research articles and one book on various topics including the estimation of optical flow and stereoscopic disparity, probabilistic methods in motion analysis, 2D visual tracking, 3D people tracking and hand tracking, modeling appearance in image sequences, physics-based models of human motion analysis, non-Fourier motion and stereo perception, and the neural basis of stereo vision. |