Team Members
The IFML team includes researchers from the University of Texas at Austin, the University of Washington, Wichita State University, and Microsoft Research.
Leadership

Adam Klivans
Director, Institute for Foundations of Machine Learning
Professor, Computer Science
University of Texas at AustinAreas of interest: Deep Learning, Graphical Models

Alex Dimakis
CoDirector, Institute for Foundations of Machine Learning
Professor, Electrical & Computer Engineering
University of Texas at AustinAreas of interest: Information theory, Coding theory, Unsupervised Machine Learning

Brent Winkelman
Managing Director, Institute for Foundations of Machine Learning
Senior Personnel

Professor, Computer Science
Areas of interest: Theoretical Computer Science; Capabilities and limits of quantum computers; Computational complexity heory

Associate Professor, Computer Science and Engineering
University of WashingtonAreas of interest: Learning with Dynamic Data, Exploiting Structure in Data, Optimizing Real World Objectives

Professor, Electrical and Computer Engineering
University of Texas at AustinAreas of interest: Advanced Algorithms for Deep Learning, Learning with Dynamic Data, Exploiting Structure in Data

Sr. Principal Research Manager
Microsoft ResearchAreas of interest: Machine Learning Theory, Optimization, Statistical Machine Learning

Professor, Electrical & Computer Engineering
University of Texas at Austin 
Associate Professor, Computer Science,
University of Texas at AustinAreas of interest: Exploiting Structure in Data, Optimizing Real World Objectives, Explainable AI

Postdoctoral Fellow, Lead of Deep Proteins group.
Areas of interest: Area of Interest: Machine Learningguided Protein Engineering and Design

Associate Professor, Computer Science
University of Texas at AustinAreas of interest: Static program analysis/verification, Program synthesis, Automated logical reasoning

Assistant Professor
University of WashingtonAreas of interest: Advanced Algorithms for Deep Learning, Exploiting Structure in Data, Optimizing Real World Objectives

Assistant Professor, Computer Science
University of Texas at Austin
Areas of interest: Deep Learning, Natural Language

Professor, School of Information
University of Texas at AustinAreas of interest: AI Ethics, Social Informatics, ValueSensitive Design

Professor, Computer Science
University of Texas at AustinAreas of interest: Deep Learning, Robotics, Vision

Senior Researcher
Microsoft Research RedmondAreas of interest: Advanced Algorithms for Deep Learning, Deep Learning, Machine Learning Theory

Associate Professor, Statistics
University of WashingtonAreas of interest: Robust statistical machine learning, Learning feature representations of complex data, Computationallyefficient optimization algorithms for learning and inference

Postdoc
PhD, Stanford UniversityAreas of interest: Optimization/Sampling, Signal Processing, Statistics

Professor, Computer Science and Engineering,
University of WashingtonAreas of interest: Reinforcement learning and controls, Representation Learning, Deep Learning

Postdoc
PhD, University of Texas at AustinAreas of interest: Visual Domain Adaptation, Unsupervised Learning, SemiSupervised Learning

Assistant Professor, Computer Science
University of Texas at AustinAreas of interest: Optimizing Real World Objectives, Deep Learning, Vision

Associate Professor, Electrical and Computer Engineering, Princeton
Areas of interest: Foundations of AI and Deep Learning, Representation Learning, Foundations of Deep Reinforcement Learning

Senior Researcher
Microsoft ResearchAreas of interest: Advanced Algorithms for Deep Learning, Machine Learning Theory, Statistical Machine Learning

Assistant Professor, Computer Science
University of Texas at AustinAreas of interest: Advanced Algorithms for Deep Learning, Learning with Dynamic Data, Exploiting Structure in Data

Associate Professor, Computer Science
UCLA Samueli School of Engineering
Areas of interest: Complexity theory, Learning theory, Algorithms, Probability theory

Assistant Professor, Electrical and Computer Engineering
University of Texas at AustinAreas of interest: Optimization, Machine Learning, Artificial Intelligence

Professor, Santa Fe Institute
Areas of interest: Problems at the interface of physics, computer science, and mathematics, such as phase transitions in statistical inference

Assistant Professor, Computer Science and Engineering
University of WashingtonAreas of interest: Learning with Dynamic Data, Active Learning, Machine Learning Theory

Assistant Professor, Computer Science
University of Texas at AustinAreas of interest: Optimizing Real World Objectives, Active Learning, Deep Learning

Associate Professor, Computer Science and Engineering
University of WashingtonAreas of interest: Advanced Algorithms for Deep Learning, Learning with Dynamic Data, Exploiting Structure in Data

Assistant Professor, Computer Science
University of Texas at Austin 
Jay Reddy
Director, Engineering Analytics
Infrastructure Solutions Group
Dell Technologies 
Alessandro Rinaldo, Professor, Department of Statistics & Data Sciences, University of Texas at Austin
Areas of interest: Theoretical properties of highdimensional statistical models

Associate Professor, Electrical & Computer Engineering
University of Texas at AustinAreas of interest: Advanced Algorithms for Deep Learning, Active Learning, Deep Learning

Assistant Professor, Statistics & Data Sciences
University of Texas at AustinAreas of interest: Large Scale Machine Learning, Machine Learning Theory, Networks

Professor
Toyota Research Institute and University of Washington (starting Fall 2021)Areas of interest: Advanced Algorithms for Deep Learning, Deep Learning, Machine Learning Theory

Professor, Electrical & Computer Engineering
University of Texas at AustinAreas of interest: Advanced Algorithms for Deep Learning, Learning with Dynamic Data, Active Learning

Associate Professor, Electrical Engineering and Computer Science
Wichita State UniversityAreas of interest: Exploiting Structure in Data, Deep Learning, Knowledge Representation

Professor, Computer Science
University of Texas at AustinAreas of interest: Learning with Dynamic Data, Exploiting Structure in Data, Optimizing Real World Objectives

Assistant Professor, Electrical & Computer Engineering
University of Texas at AustinAreas of interest: bioECE, Decision, Information, and Communications Engineering (DICE)

Assistant Professor, Mathematics
University of Texas at AustinAreas of interest: Tropical Geometry, Probability, Combinatorics, Economics, Neuroscience

Assistant Professor, Electrical and Computer Engineering
University of Texas at AustinAreas of interest: Advanced Algorithms for Deep Learning, Learning with Dynamic Data, Exploiting Structure in Data, Optimizing RealWorld Objectives

Professor, Mathematics
University of Texas at AustinAreas of interest: Advanced Algorithms for Deep Learning, Learning with Dynamic Data, Exploiting Structure in Data

Professor, Computing and Mathematical Sciences, CalTech
Areas of interest: Primarily in machine learning and spanning the entire theorytoapplication spectrum from foundational advances all the way to deployment in real systems

Postdoc
PhD, Cornell UniversityAreas of interest: Probabilistic Machine Learning, Bayesian Deep Learning

Amy Zhang
Assistant Professor, Electrical & Computer Engineering, University of Texas at Austin
Areas of interest: Reinforcement Learning, Exploiting Structure in Data, Representation Learning
Advisory Board

Pieter Abbeel
Professor, Electrical Engineering and Computer Sciences
University of California, Berkeley 
Piotr Indyk
Thomas D. and Virginia W. Cabot Professor
Department of Electrical Engineering and Computer Science
MIT 
Ravi Kumar
Principal Research Scientist
Google 
Jitendra Malk
Professor, Electrical Engineering and Computer Science
University of California, Berkeley 
Ronitt Rubinfeld
Professor, Electrical Engineering and Computer Science
MIT 
Satinder Singh
Professor, Computer Science and Engineering
University of Michigan 
Alexander Tropsha
Associate Dean for Pharmacoinformatics & Data Science
K.H. Lee Distinguished Professor, Chemical Biology and Medicinal Chemistry, Eshelman School of PharmacyUniversity of North Carolina, Chapel Hill

Manuela Veloso
Head of AI Research/Professor, AI Research
JPMorgan Chase/Carnegie Mellon University 
Rebecca Willett
Professor, Statistics and Computer Science
University of Chicago
Partners

Colleges
 College of Natural Sciences
 Cockrell School of Engineering
 School of Information
 McCombs School of Business
 College of Liberal Arts

Departments
 Department of Computer Science
 Department of Electrical & Computer Engineering
 Department of Information, Risk, and Operations Management
 Department of Linguistics
 Department of Mathematics
 Department of Psychology
 Department of Statistics & Data Science

Others
 Office of the Vice President for Research
 Oden Institute
 Texas Advanced Computing Center
 Texas Computing
 Texas Robotics
 Good Systems