Prof. Darrell (email@example.com) is on the faculty of the CS Division of the EECS Department at UC Berkeley and he is also appointed at the UC-affiliated International Computer Science Institute (ICSI). Darrell’s group develops algorithms for large-scale perceptual learning, including object and activity recognition and detection, for a variety of applications including multimodal interaction with robots and mobile devices. His interests include computer vision, machine learning, computer graphics, and perception-based human computer interfaces. Prof. Darrell was previously on the faculty of the MIT EECS department from 1999-2008, where he directed the Vision Interface Group. He was a member of the research staff at Interval Research Corporation from 1996-1999, and received the S.M., and PhD. degrees from MIT in 1992 and 1996, respectively. He obtained the B.S.E. degree from the University of Pennsylvania in 1988, having started his career in computer vision as an undergraduate researcher in Ruzena Bajcsy's GRASP lab.
Rómer Rosales received a Ph.D. in Computer Science from Boston University and later joined the University of Toronto and the Massachusetts Institute of Technology as Research Associate in Machine Learning. Since 2005 he has held various scientific positions in industry and help found a consumer healthcare start-up as chief scientist. Currently he is the head of Growth and Ecosystem Relevance at LinkedIn focusing on applying machine learning and optimization to help LinkedIn create economic opportunity. He has published over 60 articles in Machine Learning, Data Mining, and Computer Vision conferences and journals, and holds more than 12 US patents. He has served as Chair, senior committee member, and guest editor in these fields.
Yoshua Bengio is Full Professor of the Department of Computer Science and Operations Research, head of the Montreal Institute for Learning Algorithms (MILA), CIFAR Program co-director of the CIFAR Neural Computation and Adaptive Perception program, Canada Research Chair in Statistical Learning Algorithms. His main research ambition is to understand principles of learning that yield intelligence. He teaches a graduate course in Machine Learning (IFT6266) and supervises a large group of graduate students and post-docs. His research is widely cited (over 40000 citations found by Google Scholar in mid-2016, with an H-index of 84). Yoshua Bengio is currently action editor for the Journal of Machine Learning Research, associate editor for the Neural Computation journal, editor for Foundations and Trends in Machine Learning, and has been associate editor for the Machine Learning Journal and the IEEE Transactions on Neural Networks. Yoshua Bengio was Program Chair for NIPS'2008 and General Chair for NIPS'2009 (NIPS is the flagship conference in the areas of learning algorithms and neural computation). Since 1999, he has been co-organizing the Learning Workshop with Yann Le Cun, with whom he has also created the International Conference on Representation Learning (ICLR). He has also organized or co-organized numerous other events, principally the deep learning workshops and symposiua at NIPS and ICML since 2007.