Invited Talks
2025
- NSF IAIFAI Colloquium — (MIT/Harvard, USA)
Flow Equivariance: Enforcing Time-Parameterized Symmetries in Sequence Models (link to recording) - Fields Symposium on Spatiotemporal Neural Dynamics — (University of Toronto, Canada)
The Computational Inductive Biases of Spatiotemporal Artificial Neural Networks (link to recording) - Neuro AI Emerging Leaders Webinar — (Virtual)
The Computational Inductive Biases of Spatiotemporal Dynamics (link to recording) - AI, Brain, & Cognition Seminar, Center for NeuroImaging Research — (Virtual: Seoul, South Korea)
Computational Inductive Biases of Spatiotemporal Dynamics - Miller Lab Reading Group — (MIT, USA)
Spatiotemporal Dynamics in RNNs as Flow Equivariance - Guest Lecture: Applied Math 220, Geometric Deep Learning @ Harvard — (Harvard, USA)
Flow Equivariance - Flagship Pioneering — (Boston, USA)
Flow Equivariance: Enforcing Time-Parameterized Symmetries in Sequence Models - Shine Lab Group Meeting — (Virtual: Sydney, Australia)
A Spatiotemporal Perspective on Dynamical Computation - Harvard SEAS Workshop on Structured Learning in Vision, Imaging, and Robotics — (Harvard, USA)
Flow Equivariance in Embodied Visual Systems
2024
- NeurReps International Speaker Series — (Virtual)
A Spacetime Perspective on Neural Information Processing Systems (link to recording) - Woods Hole Computational Neuroscience Workshop — (Telluride, USA)
Wave Information Processing Systems (link to recording) - Yale Wu Tsai Neuro AI Seminar — (New Haven, CT, USA)
A Spacetime Perspective on Neural Information Processing Systems - Computational Neuroscience Next Generation Symposium — (Wash. U. St. Louis, MO, USA)
A Spacetime Perspective on Neural Information Processing Systems - CERN CMS Machine Learning Seminar — (Virtual: Geneva, Switzerland)
Traveling Waves in Brains and Machines - Fiete Lab Group Meeting — (MIT, USA)
Natural Representational Structure - Kanwisher Lab Group Meeting — (MIT, USA)
Topographic Generative Models - CSML Reading Group — (Imperial College London, UK)
Traveling Waves in Brains and Machines
2023
- Active Inference Institute Seminar — (Virtual)
Natural Structure in Artificial Neural Networks (link to recording) - Frankfurt Institute for Advanced Studies, Giersch School and International Conference on Complex Systems — (Frankfurt, Germany)
Generalized Equivariance through Fluid Representations in Brains and Machines - A.D. de Groot Cognitive AI Lecture — (Amsterdam, Netherlands)
Topographic Organization and Traveling Waves as Natural Representational Structure for Artificial Neural Networks - Workshop on Structured Learning, Chalmers AI Research Center — (Gothenburg, Sweden)
Natural Neural Structure for Artificial Intelligence - Salk Institute Computational Neurobiology Lab Group Meeting — (La Jolla, CA, USA)
Traveling Waves Encode the Recent Past and Enhance Sequence Learning - EPFL Laboratory for Computational Neuroscience — (Virtual: Lausanne, Switzerland)
Naturally Structured Representations in Artificial Neural Networks - BINDS Reading Club — (UMass Amherst, USA)
Traveling Waves Encode the Recent Past and Enhance Sequence Learning
2022
- Geometric Deep Learning Seminar — (Amsterdam, Netherlands)
Topographic Generative Models Learn Structured Representations (link to recording) - Seminar on Advances in Probabilistic Machine Learning — (Virtual: Aalto University, Finland)
Topographic Variational Autoencoders Learn Equivariant Capsules
2021
- Bosch Center for AI Workshop on Deep Probabilistic Models — (Renningen, Germany)
Self-Normalizing Flows - Debora Marks Lab Group Meeting — (Virtual: Harvard, USA)
Equivariance & Topographic Generative Models - Intel Deep Learning Community of Practice — (Virtual: Santa Clara, CA, USA)
Topographic Generative Models Learn Structured Representations