Team Members

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

Connect With Us

Leadership

  • Adam Klivans

    Adam Klivans

    Director, Institute for Foundations of Machine Learning
    Professor, Computer Science
    University of Texas at Austin

    Areas of interest: Deep Learning, Graphical Models

  • Alex Dimakis

    Alex Dimakis

    Co-Director, Institute for Foundations of Machine Learning 
    Professor, Electrical & Computer Engineering
    University of Texas at Austin

    Areas of interest: Information theory, Coding theory, Unsupervised Machine Learning

Senior Personnel

  • Associate Professor, Computer Science and Engineering
    University of Washington

    Areas of interest: Learning with Dynamic Data, Exploiting Structure in Data, Optimizing Real World Objectives

  • Professor, Electrical and Computer Engineering
    University of Texas at Austin

    Areas of interest: Advanced Algorithms for Deep Learning, Learning with Dynamic Data, Exploiting Structure in Data

  • Sr. Principal Research Manager
    Microsoft Research

    Areas 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 Austin

    Areas of interest: Exploiting Structure in Data, Optimizing Real World Objectives, Explainable AI

  • Associate Professor, Computer Science 
    University of Texas at Austin

    Areas of interest: Static program analysis/verification, Program synthesis, Automated logical reasoning

  • Assistant Professor
    University of Washington

    Areas 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 Austin

    Areas of interest: AI Ethics, Social Informatics, Value-Sensitive Design

  • Professor, Computer Science
    University of Texas at Austin

    Areas of interest: Deep Learning, Robotics, Vision

  • Senior Researcher
    Microsoft Research Redmond

    Areas of interest: Advanced Algorithms for Deep Learning, Deep Learning, Machine Learning Theory

  • Associate Professor, Statistics 
    University of Washington

    Areas of interest: Robust statistical machine learning, Learning feature representations of complex data, Computationally-efficient optimization algorithms for learning and inference

  • Postdoc
    PhD, Stanford University

    Areas of interest: Optimization/Sampling, Signal Processing, Statistics

  • Professor, Computer Science and Engineering, 
    University of Washington

    Areas of interest: Reinforcement learning and controls, Representation Learning, Deep Learning

  • Postdoc
    PhD, University of Texas at Austin

    Areas of interest: Visual Domain Adaptation, Unsupervised Learning, Semi-Supervised Learning

  • Assistant Professor, Computer Science 
    University of Texas at Austin

    Areas of interest: Optimizing Real World Objectives, Deep Learning, Vision

  • Senior Researcher
    Microsoft Research

    Areas of interest: Advanced Algorithms for Deep Learning, Machine Learning Theory, Statistical Machine Learning

  • Assistant Professor, Computer Science
    University of Texas at Austin

    Areas of interest: Advanced Algorithms for Deep Learning, Learning with Dynamic Data, Exploiting Structure in Data

  • Assistant Professor, Electrical and Computer Engineering
    University of Texas at Austin

    Areas of interest: Optimization, Machine Learning, Artificial Intelligence

  • Assistant Professor, Computer Science and Engineering
    University of Washington

    Areas of interest: Learning with Dynamic Data, Active Learning, Machine Learning Theory

  • Assistant Professor, Computer Science
    University of Texas at Austin

    Areas of interest: Optimizing Real World Objectives, Active Learning, Deep Learning

  • Associate Professor, Computer Science and Engineering
    University of Washington

    Areas of interest: Advanced Algorithms for Deep Learning, Learning with Dynamic Data, Exploiting Structure in Data

  • Assistant Professor, Computer Science 
    University of Texas at Austin

  • Associate Professor, Electrical & Computer Engineering
    University of Texas at Austin

    Areas of interest: Advanced Algorithms for Deep Learning, Active Learning, Deep Learning

  • Assistant Professor, Statistics & Data Sciences
    University of Texas at Austin

    Areas 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 Austin

    Areas of interest: Advanced Algorithms for Deep Learning, Learning with Dynamic Data, Active Learning

  • Associate Professor, Electrical Engineering and Computer Science
    Wichita State University

    Areas of interest: Exploiting Structure in Data, Deep Learning, Knowledge Representation

  • Professor, Computer Science 
    University of Texas at Austin

    Areas of interest: Learning with Dynamic Data, Exploiting Structure in Data, Optimizing Real World Objectives

  • Assistant Professor, Electrical & Computer Engineering
    University of Texas at Austin

    Areas of interest: bioECE, Decision, Information, and Communications Engineering (DICE)

  • Assistant Professor, Mathematics
    University of Texas at Austin

    Areas of interest: Tropical Geometry, Probability, Combinatorics, Economics, Neuroscience

  • Assistant Professor, Electrical and Computer Engineering
    University of Texas at Austin

    Areas of interest: Advanced Algorithms for Deep Learning, Learning with Dynamic Data, Exploiting Structure in Data, Optimizing Real-World Objectives

  • Professor, Mathematics
    University of Texas at Austin

    Areas of interest: Advanced Algorithms for Deep Learning, Learning with Dynamic Data, Exploiting Structure in Data

  • Postdoc
    PhD, Cornell University

    Areas of interest: Probabilistic Machine Learning, Bayesian Deep Learning

Advisory Board

  • Pieter Abbeel

    Professor, Electrical Engineering and Computer Sciences
    University of California, Berkeley

  • Pedro Felzenszwalb

    Professor, School of Engineering and Department of Computer Science
    Brown University

  • 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

  • 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

We are proud to be engaged in research projects with the following industrial and governmental 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