Events

Title: Dynamical models of neural-behavioral data with application to AI-driven neurotechnology Abstract: A major challenge in neuroAI is to model, decode, and modulate the activity of large populations of neurons that underlie our brain’s functions and dysfunctions. Toward addressing this challenge, I will present our work on novel dynamical models of neural-behavioral data and applying…

Title and Abstract: TBD

Title: Building the brain’s efficient system-level architecture: optimisations across space, time, and multiple regions Abstract: The computations a brain can perform are fundamentally constrained by physical realities: energetic resources are limited, and time is precious. To understand why the brain works the way it does, we must understand its function in the context of these…

Title: Learning representations of specifics and generalities over time Abstract: There is a fundamental tension between storing discrete traces of individual experiences, which allows recall of particular moments in our past without interference, and extracting regularities across these experiences, which supports generalization and prediction in similar situations in the future. One influential proposal for how the…

Continuation from prior meetings about benchmarks and competition proposals. Zoom Link: upon request @ [email protected]

Next Meeting Info Date: Monday, October 27 Time: 3-4pm Room: CEPSR 620 Zoom: Upon request @[email protected]

Bio: Leila Wehbe is an associate professor in the Machine Learning Department and the Neuroscience Institute at Carnegie Mellon University. Her work is at the interface of cognitive neuroscience and computer science. It combines naturalistic functional imaging with machine learning both to improve our understanding of the brain and to find insight to build better artificial systems. She is…

Seminar Time: 11:30am Date: Fri 11/7/25 Seminar Location: JLG, L5-084 Host: Weijia Zhang Title: Latent causes, prediction errors, and the organization of memory Abstract: No two events are alike. But still, we learn, which means that we implicitly decide what events are similar enough that experience with one can inform us about what to do in another. We have suggested…

Bio Bryan Li is completing his PhD in NeuroAI at the University of Edinburgh, under the supervision of Arno Onken and Nathalie Rochefort. His main PhD project focuses on building deep learning-based encoding models of the visual cortex that accurately predict neural activity in response to arbitrary visual stimuli. Recently, he joined Dario Farina’s lab at…

Continuation from prior meetings about benchmarks and competition proposals. Zoom Link: upon request @ [email protected]

Next Meeting Info Date: Wednesday, Nov 12 Time: 4pm-5pm Room: CEPSR 620 Zoom: Upon request @ [email protected]

Aaron Hertzmann Why Do Pictures Work? Explanations From Real-World Vision Speaker: Aaron Hertzmann (Adobe) Host: Carl Vondrick Date: Thursday, November 13, 2025 Time: 2:30 PM Location: CSB 453 Abstract: I outline possible answers to the long-standing question of why pictures work: why can people look at a painting or photograph, and see a depicted subject, rather than just marks…