Guillaume Lajoie is an assistant professor in the Department of Mathematics and Statistics (DMS) at the Université de Montréal. Before that, he was a postdoctoral fellow at the Max Planck Institute for Dynamics and Self-Organization and at the University of Washington Institute for Neuroengineering. He obtained his PhD from the Department of Applied Mathematics at the University of Washington, in Seattle.
His research focusses on the relationship between network dynamics and computations, with applications in applied mathematic, theoretical neuroscience, machine learning and neuroengineering. Recent work include the development of a theory linking chaotic dynamics to information content in signal driven recurrent networks, as well as the development of computational models to optimize bidirectional brain-computer interfaces.
