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

AI Master’s Program Launches With Ability to Serve Thousands
The University of Texas at Austin is launching a new online master’s program in AI with the potential to bring thousands of new students into the field.
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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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IFML Public Lecture: AI for Accurate and Fair Imaging
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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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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
- January26January27
Responsible Machine Learning's Causal Turn: Promises and Pitfalls
Talk by Zachary Lipton, PhD, Assistant Professor, Carnegie Mellon University
February3Machine Learning on Large-Scale Graphs
Talk by Luana Ruiz, PhD
February10Activation Function Design for Deep Networks: Linearity and Effective Initialisation
Talk by Jared Tanner, PhD, Professor of Mathematics of Information, University of Oxford
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