Program & Schedule

Learning Dynamics in Natural & Artificial Intelligence

September 2-4, 2026

Program

The Learning Dynamics workshop is a three-day conference featuring podium presentations and discussions with expert speakers, a poster reception, and opportunities for discussion amongst participants.

This workshop will convene researchers from artificial intelligence, neuroscience, cognitive science, and related disciplines to examine the principles governing learning and training dynamics across natural and artificial systems. 

Speakers
Speaker Abstracts
Poster Presentations

Schedule

Wednesday, September 2nd, 2026

Start TimeEvent
9:30 AMRegistration Check-in Opens
10:00 AMWelcoming Remarks
10:10 AMErin Hecht: “How evolution shapes the capacity to learn“
10:55 AMVenki Murthy: “An inductive bias for generalization in mouse olfactory learning“
11:40 AMRuiyi Zhang: “Resource constraints externalize memory in brains and machines“
11:55 AMNavid Shervani-Tabar: “Emergent Traveling Waves in Neural Circuits“
12:10 PMLunch
1:40 PMNidhi Seethapathi: “Viability determines the structure and efficiency of motor practice”
1:55 PMBence Ölveczky: “Using neuro-biomechanical simulations to probe neural control of learned skills“
2:40 PMLilach Avitan: “Brain-wide neural underpinnings of social behavior in zebrafish“
3:25 PMBreak
4:00 PM – 6:00 PMPoster Reception (Refreshments will be served)

Thursday, September 3rd, 2026

Start TimeEvent
9:30 AM Registration Check-in Opens
10:00 AMKarolina Dziugaite: “The Dynamics of Memorization in Deep Learning“
10:45 AMJulia Kempe: “Who Teaches the Teacher? Self-Improving Reasoning Systems“
11:30 AMCole Gibson: “Distinct mechanisms underlying in-context learning in transformers“
11:45 AMLukas Vogelsang: “Degraded early visual input shapes holistic perceptual organization in humans and deep networks“
12:00 PMLunch
1:30 PMMarin Vogelsang: “Developmental temporal degradation as a scaffold for robust video classification“
1:45 PMHouman Safaai: “How dendritic trees shape local learning and route credit“
2:00 PMAditi Raghunathan: “Disentangling memorization from generalization by design” 
2:45 PMBreak
3:30 PMAlice Wang: “What the connectome teaches us about lottery-ticket signs“
3:45 PMSurya Ganguli: “How much data do we need to imagine new images and learn language?”
4:30 PMClosing remarks

Friday, September 4, 2026

Start TimeEvent
9:30 AMRegistration Check-in Opens
10:00 AMDileep George: TBA
10:45 AMDevon Jarvis: “The Dynamics of Language Evolution from Humans to LLMs“
11:30 AMNima Dehghani: “Evolutionary Optimization Reveals Structural Constraints on Reservoir Architecture for Spatiotemporal Chaos“
11:45 AMLindsay Smith: “Learning long-ranged structure in English: Code length and entropy dynamics during LLM training“
12:00 PMLunch
1:30 PMAnthony Zador: “From Connectome to Computation”
2:15 PMLeslie Valiant: “Enhanced and Efficient Reasoning in Large Language Models“
3:00 PMClosing Remarks
Poster Presentations
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