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pouya.bashivan [at] mcgill.ca |
Research area: computational systems neuroscience
Research description:
Much of our intelligent behavior and even our own characters rely on memory — the ability to remember past experiences and to bind information scattered over time, readily deployable to guide our actions. The human memory has been the topic of numerous studies over decades, providing an extensive description of its various forms, the relationship between them, the anatomical structures supporting each, and the conditions under which each one is engaged. Yet, we still lack computational models that could explain and predict many of the neural and behavioral observations that have been made over the years. My lab seeks to develop models and algorithms that can explain, predict, and ultimately regulate the brain responses (in the form of neural responses and the consequent behaviors) during visual tasks, specially ones that require short- and long-term memory. Our research builds on top of various tools and theories developed in machine learning, neuroscience and cognitive science. Developing computational models are becoming increasingly important in elevating our understanding of the neural processes supporting different behaviors, as well as for paving the way towards translating neuroscience into life-changing applications.
Academic experience:
Postdoc: (Machine Learning) Montreal Institute for Learning Algorithms, Canada, 2020
Postdoc: (Computational Neuroscience) Massachusetts Institute of Technology, USA, 2016-2020
Ph.D.: (Computer Eng.) University of Memphis, USA, 2012-2016
B.Sc., M.Sc. (Elec. and Control Eng.), Khaje-nasir Toosi University of Technology, Iran, 2001-2009
Publications: Google Scholar