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 Events

IFML Seminar: Optimization Challenges in Adversarial Machine Learning
Abstract: Thanks to neural networks (NNs), faster computation, and massive datasets, machine learning (ML) is under increasing pressure to provide automated solutions to even harder real-world tasks beyond human performance with ever faster response...
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Article
Adam Klivans and Alex Dimakis on KXAN News!
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Event
IFML Seminar: How to Measure the Depth in a Fully Connected Network?
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Article
Joint FAI/ML+X Talk with Peter Stone: Outracing Champion Gran Turismo Drivers with Deep Reinforcement Learning
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Event
Deployable Robots that Learn
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Article
‘Off Label’ Use of Imaging Databases Could Lead to Bias in AI Algorithms
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Research Project
Fairness in Imaging with Deep Learning
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Upcoming Events and Workshops
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April29
IFML Seminar: Optimization Challenges in Adversarial Machine Learning
Talk by Volkan Cevher, Associate Professor, Swiss Federal Institute of Technology Lausanne and Faculty Fellow, Electrical and Computer Engineering, Rice University