Neurogenesis Speaker Series
Neurogenesis Speaker Series
Wednesday, February 5, 2025
4:30鈥�5:30 p.m. (with post-event reception)
The听Neurogenesis听Speaker Series will give you the opportunity to get to know HBHL鈥檚 new recruits firsthand, learn about their research, ask questions and network with your peers during the post-event reception.
Each event in this series will feature two HBHL faculty recruits whose research areas provide an interesting contrast or intersection for discussion.
December's Speakers:听
- Paul Masset, PhD听-听TBD
- Pouya Bashivan, PhD听-听TBD
Speakers
Paul Masset
Paul Masset is an Assistant Professor in the Department of Psychology at McGill University and an Affiliate member at Mila - Quebec Artificial Intelligence Institute, working at the intersection of neuroscience, AI and cognitive science. The focus of his research group is to understand how the structure of neural circuits endows the brain with efficient distributed computations underlying cognition and how we can leverage these principles to design more efficient learning algorithms.听Prior to joining McGill, he was a Postdoctoral Fellow at Harvard University. He obtained his PhD at Cold Spring Harbor Laboratory, his Masters in Cognitive Science at the 脡cole des hautes 茅tudes en sciences sociales 听(EHESS) and his M.Eng/B.A. in Information and Computer Engineering at the University of Cambridge.
Pouya Bashivan
Pouya Bashivan is an Assistant Professor at the Department of Physiology at McGill University, an associate member of Mila, the Quebec AI Institute, and a William Dawson Scholar. Bashivan鈥檚 past research has spanned the fields of control theory, machine learning, and neuroscience. The research in his group is at the intersection of artificial neural networks and neuroscience and is focused on developing computational models of visual processing in the primate brain with a focus on visual memory. Specifically, he uses artificial neural network models trained to perform ecologically-relevant tasks to model the cortical responses in primate鈥檚 brain. His ultimate research goal is to leverage the predictive power in such models of brain activity to modulate the brain鈥檚 function in disease.
