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.
Featured
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Article
THIS JUST IN: New York Times Story on UT Austin's Online Master's Degree in AI
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Article
IFML Public Lecture: AI for Accurate and Fair Imaging
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Article
Shiwei Liu and Visual Informatics Group Receive Best Paper Award at LoG 2022
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Article
NLP Modules for High School
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Article
IFML Researchers Win Two Outstanding Paper Awards at NeurIPS 2022
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Research Project
Exploiting Shared Representations for Personalized Federated Learning
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Upcoming Events and Workshops
- March24
IFML Seminar: Mutual Learning in Brain-Machine Interfaces
Talk by José del R. Millán, Professor, Department of Neurology at Dell Medical School, Associate Director of Texas Robotics
March31IFML Seminar: Variational Autoencoding Neural Operators
Talk by Paris Perdikaris, PhD, Assistant Professor, University of Pennsylvania
March31IFML Seminar: What Makes Data Suitable For Deep Learning?
Talk by Nadav Cohen, Assistant Professor, Tel Aviv University
Previously Recorded Talks
New & Noteworthy
Research Project
SCALP - Supervised Contrastive Learning for Cardiopulmonary Disease Classification and Localization in Chest X-rays using Patient Metadata
Use-Inspired Applications