CAFÉ Distinguished Lecture Series: Artificial Intelligence meets Neuroscience

AI systems have made rapid progress in achieving parity with or even exceeding human performance in specialized tasks, most impressively in extracting visual information from images through object detection, classification, and caption generation. Nevertheless, performance still lags humans and even lower animals in otherwise basic tasks that involve novelty and generalization: handling unanticipated tasks and new environments, learning rapidly without supervision, deducing the unobserved, and anticipating likely outcomes. This lecture series focuses on efforts at the intersection of AI and human cognition towards a better understanding of cognition in the brain and applying that understanding to designing cognitive AI systems. The lecture series will feature neuroscience, computer science, and electrical engineering experts. The lecture series is open to the public.

February 14
Re-Engineering Computing with Neuro-Inspired Learning: Algorithms, Circuits, and Systems
Kaushik Roy, Edward G. Tiedemann, Jr., Distinguished Professor of Electrical and Computer Engineering, Purdue University
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February 15
Memory, Cognition, and the Role of Sleep
Matthew Wilson, Sherman Fairchild Professor in Neurobiology, MIT
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February 16
Neuroscience-Inspired Machine Learning
Laurent Itti, Professor of Computer Science, Psychology and Neuroscience, University of Southern California Viterbi School
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February 17
Diminishing Returns with Deep Neural Networks
Mehrdad Mahdavi, Dorothy Quiggle Career Development Assistant Professor of Computer Science & Engineering, Penn State
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February 18
Vision and Language Understanding
Huijuan Xu, Assistant Professor of Computer Science & Engineering, Penn State 
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February 21
Sound Symbolism and Its Neural Basis
Krishnankutty Sathian, Professor of Neurology, Neural & Behavioral Sciences, and Psychology and Director, Neuroscience Institute, Penn State
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