Machine Learning and Friends Lunch
Machine Learning and Friends Lunch: Sherry Yang, Learning World Models and Agents for High-Cost Environments
Machine Learning and Friends Lunch featuring Sherry Yang, Assistant Professor of Computer Science at NYU Courant and
a scientist at Google DeepMind.
Machine Learning and Friends Lunch: Ryan Louie, Adapting LLMs to Upskill Novices for High-Stakes Domains
Ryan Louie is a postdoctoral researcher in the Computer Science Department at Stanford University.
Machine Learning and Friends Lunch: Sherry Wu, Making AI Systems Work for Imperfect Humans
Machine Learning and Friends Lunch featuring Sherry Wu, assistant professor at the Human-Computer Interaction
Institute at Carnegie Mellon University.
Machine Learning and Friends Lunch: Eugene Vinitsky, Robust Autonomy Emerges from Self-Play
This talk explains how self-play can train autonomous driving systems in simulation, achieving realistic and robust performance without human data.
Machine Learning and Friends Lunch: Mingyu Derek Ma, Elevating Large Language Models to Expert Intelligence
LLMs aid science but struggle to generalize. This talk explores capturing expert intuition and building agents for complex scientific reasoning.
Machine Learning and Friends Lunch: Wei-Chiu Ma, Towards Physically-Grounded Digital Twins and Beyond
Machine Learning and Friends Lunch featuring Wei-Chiu Ma, an Assistant Professor of Computer Science at Cornell
University.
Machine Learning and Friends Lunch: Aaron Mueller, Time- and Context-Aware Interpretability
Aaron Mueller is an assistant professor of Computer Science and, by courtesy,
of Data Science at Boston University.
Machine Learning and Friends Lunch: Yuanqi Du, Scientific Knowledge Emerges in LLMs and You Can Extract It
Yuanqi Du is a PhD candidate in Computer Science at Cornell University, where he studies the intersection of AI and scientific discovery.
Machine Learning and Friends Lunch: Dana Arad, Sparse Autoencoders for Content Control
Machine Learning and Friends Lunch featuring Dana Arad, a CS PhD candidate at the Technion.
Machine Learning and Friends Lunch: R. Kenny Jones, Designing DSLs for 3D Shape and Scene Generation
Neurosymbolic 3D generation depends on DSLs that can be learned from data or co-designed with LLMs.
Machine Learning and Friends Lunch: Tianmin Shu, Scaling Model-based Theory of Mind for Socially Intelligent Embodied Partners
Talk on building AI Theory of Mind using cognitive and foundation models to improve interaction, collaboration, and real-world reasoning.
Machine Learning and Friends Lunch: Michael Boratko, Representational Capacity of Vector Embeddings for Retrieval
Machine Learning and Friends Lunch featuring Michael Boratko, a research scientist at Google DeepMind.