Ã山ǿ¼é

Pouya Bashivan - Assistant Professor

Ã山ǿ¼é

Pouya Bashivan


Department of Physiology                                                                                                               
Ã山ǿ¼é
McIntyre Medical Sciences Building, Room 1117
3655 Promenade Sir William Osler
Montréal, Québec H3G 1Y6
514-398-8310

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:

Back to top