Associative memories, Categorization, Classification, Feature extraction, Invariance.
Although it is something most of us do every day without effort, memorizing is in fact an incredibly complex task. For instance, the simple act of storing and retrieving a given perceptual pattern is something a computer cannot do with anything approaching human efficiency and robustness.
Dr. Chartier aims to better understand how human cognitive system accomplishes the complex task of create (and enhance) representations from patterns as well as recognize, identify, categorize and classify them. In particular, his research focuses on using the nonlinear dynamics system perspective into artificial neural networks where memories are represented as invariant states of the network. His main objective is the development of recurrent associative memories that can take into account both supervised and unsupervised learning while being constrained by neuropsychological data. From models development, it is hope that we will have a better understanding on how the brains work.
Dr. Sylvain Chartier received the B.A. degree from the University of Ottawa, in 1993 and the B.Sc. and Ph.D. degrees from the Université du Québec à Montréal, in 1996 and 2004, respectively, all in psychology. His doctoral thesis was on the development of an artificial neural network for autonomous categorization. From 2004 to 2007, Dr. Chartier was post-doctoral fellow at the Centre de recherche de l’Institut Philippe-Pinel de Montréal where he conducted research on eye-movement analysis and classification. Since 2007, He is an Assistant Professor at the University of Ottawa.
See Sylvain's Personal Website.