[Zoom Seminar] "Brain-Motivated Computation: A Journey from Neural Circuitry to Cognitive Control Systems" by Dr. Alexander G. Ororbia II, Rochester Institute of Technology

Date

Wednesday, June 28, 2023 - 10:00 to 11:00

Location

Zoom (details below)

Description

 

Dr. Alexander G. Ororbia II
Director, Neural Adaptive Computing Laboratory
Assistant Professor, Department of Computer Science
Rochester Institute of Technology, Rochester, NY, USA
Google Scholar NAC Laboratory Page

Zoom URL: https://oist.zoom.us/j/94680485435?pwd=dU9hZzZsQ0VTdVlZckM0eHd6UVM4QT09

Meeting ID: 946 8048 5435
Passcode: 598232

VIDEO


Title: "Brain-Motivated Computation: A Journey from Neural Circuitry to Cognitive Control Systems"

Abstract:  In this talk, I will examine advancements in brain-motivated computation that have been made by my group, the Neural Adaptive Computing (NAC) laboratory, over the last decade. Specifically, I will discuss the path towards robust, neurobiologically-plausible inference and credit assignment that has been explored, characterizing and contextualizing several of NAC's key developments and discoveries with respect to predictive coding circuitry, active inference, and neural cognitive control. The talk will further present generalizations to spike-level communication and information processing, some recent investigations of self-supervised, forward-only inference and learning, as well as results in simulated neurorobotics and generative modeling.

 

Bio:  Alex received the Bachelor of Science degree in Computer Science & Engineering at Bucknell University, minoring in Philosophy and Mathematics, in 2013, and his Ph.D. in Information Sciences & Technology at Penn State University, minoring in Social Data Analytics, in 2018. He is presently an Assistant Professor in Computer Science, an affiliate Professor in Psychology, and affiliate faculty in Computational Neuroscience at the Rochester Institute of Technology. Alex is also the director of the Neural Adaptive Computing (NAC) Laboratory. His research focuses on spiking neural networks, predictive coding, active inference, neurobiological credit assignment, cognitive control architectures, and neurorobotics.

All-OIST Category: 

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