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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Upcoming Events and Workshops

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Previously Recorded Talks

  • Yes, Generative Models are the New Sparsity

    Alex Dimakis, UT Austin

  • Multi-Modal Deep Learning of Electrocardiograms for Precision Cardiovascular Health

    Benjamin Glicksberg, Assistant Professor, Icahn School of Medicine at Mount Sinai

  • Clustering Mixtures with Almost Optimal Separation in Polynomial Time

    Allen Liu, graduate student in EECS at MIT.

  • Optimal Control for Electroceutical Therapies

    Joshua Chang, M.D., Ph.D., Assistant Professor, Department of Neurology, The University of Texas at Austin