Machine Learning and Friends Lunch

Machine Learning and Friends Lunch featuring Wei-Chiu Ma, an Assistant Professor of Computer Science at Cornell University.

Aaron Mueller is an assistant professor of Computer Science and, by courtesy, of Data Science at Boston University.

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 featuring Dana Arad, a CS PhD candidate at the Technion.

Neurosymbolic 3D generation depends on DSLs that can be learned from data or co-designed with LLMs.

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 featuring Michael Boratko, a research scientist at Google DeepMind.

David Burt is a postdoc in Professor Tamara Broderick’s group at the MIT Laboratory For Information and Decision Systems.

David Held is an Associate Professor at Carnegie Mellon University in the Robotics Institute and is the director of the RPAD lab: Robots Perceiving And Doing.

Karin de Langis, PhD candidate at University of Minnesota, studies artificial cognition in LLMs, explaining failures and comparing cognitive control vs humans.

Analyze Transformer attention via QK space, decomposing it into low-rank, interpretable features that explain why tokens attend and how attention scores arise.

Robot dexterity needs more than scale: I’ll show how structured affordance, contact, and motion reasoning links foundation models to open-world control.