We are the National AI Institute for Foundations of Machine Learning (IFML)

Designated by the National Science Foundation (NSF) in 2020, IFML develops the key foundational tools for the next decade of AI innovation. Our institute comprises researchers from The University of Texas at Austin, University of Washington, Wichita State University, and Microsoft Research.

Our researchers create new algorithms that can help machines learn on the fly, change their expectations as they encounter people and objects in real life, and even bounce back from deliberate attempts by adversaries to manipulate datasets.

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IFML Seminar

Foundation Model for Sequential Decision-Making

Abstract: Sequential decision-making (SDM) is crucial for adapting machine learning to dynamic real-world scenarios such as fluctuating markets or evolving healthcare, requiring models that can effectively navigate ongoing changes. Foundation models, akin to those...

Event Details

Upcoming Events and Workshops

Previously Recorded Talks

  • AIHealthTalk: 3/20/24 - How LLMs Might Help Scale World Class Healthcare to Everyone

    Vivek Natarajan, Research Scientist, Google Health

  • AIHealthTalk : 4/10/24 - Towards Digital Twins for Cardiovascular Health: From Clinical To Remote

    Bobak Mortazavi, Associate Professor, Texas A&M University

  • IFML Seminar: 4/5/24 - Robustness in the Era of LLMs: Jailbreaking Attacks and Defenses

    Hamed Hassani, Associate Professor, The University of Pennsylvania

  • AIHealthTalk : 3/27/24 - Shaping the Creation and Adoption of Large Language Models in Healthcare

    Nigam Shah, Professor, Stanford University