Our Research

Our researchers develop novel statistics and machine learning methods to accelerate scientific discovery.

Discoveries in our department, based on inferences and decisions from the data all around us, deliver research advances with a real-world impact in health care, finance, public life, technology and science.

Research Strengths

  • Algorithmic Fairness
  • Bayesian Statistics
  • Causal Inference
  • Longitudinal Analysis
  • Monte Carlo and MCMC Methods
  • Network Analysis
  • Nonparametric Methods  
  • Spatial and Spatio-Temporal Statistics
  • Statistical/Machine Learning
  • Time-Series Analysis

Centers, Institutes and Initiatives

Statistics and Data Sciences researchers participate in interdisciplinary efforts across campus to advance insights in areas such as machine learning, epidemiology and population research. 

  • Center for Health & Environment: Education and Research (CHEER) is a  hub for multidisciplinary environmental health sciences research and education, bringing together experts from across UT Austin. 
  • Good Systems is working to establish a framework for evaluating, developing, implementing and regulating AI-based technologies so they reflect human values. It is a UT Austin Grand Challenge and part of its Bridging Barriers initiative. 
  • Hobby-Eberly Telescope Dark Energy Experiment (HETDEX) represents a major UT Austin-led research initiative with TACC, the McDonald Observatory and faculty experts from across astronomy, physics, statistics and data sciences and more.
  • Machine Learning Laboratory includes computer scientists, engineers, data scientists, statisticians and mathematicians from across campus and serves as the academic home for the NSF-funded Institute for Foundations of Machine Learning.
  • Population Research Center includes researchers from across campus in areas such as demography; education, work and inequality; and population and reproductive health.
  • Texas Advanced Computing Center (TACC) is home to the world's most powerful university supercomputer.

 

Research News

Research

Vulnerable Neighborhoods Bore Brunt of Pandemic Well into its Second Year

A study in PLOS Computational Biology from University of Texas at Austin epidemiologists examined COVID infection and hospitalization rates by zip code.

A map of Travis County shows different Zip codes in different colors against a grid. Lines intersect higher and lower income areas.

UTexas News

Moving From Distressed Areas to Better-Resourced Neighborhoods Improves Kids’ Asthma

Roger Peng, a professor in the Department of Statistics and Data Sciences, contributed to a new study of childhood asthma in JAMA.

A family carries boxes into their new home

Research

Care Experiences Are Worse in For-Profit Hospices Than in Not-for-Profit Hospices, Study Finds

Patients receiving care from for-profit hospices have substantially worse care experiences than patients who receive care from not-for-profit hospices, according to a new study from RAND Corporation and a University of Texas at Austin researcher.

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Features

Why Every Generation Needs to Care About Medicare

Policy decisions centered on the federal health insurance program can have a wide-ranging impact.

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Research

Health Benefits of Wind Power Rely on Which Fossil Fuel Plants It Replaces

Health benefits of using wind energy instead of fossil fuels could quadruple if the most polluting power plants are selected for dialing down, new study...

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Research

Seven Natural Sciences Faculty Receive NSF CAREER Awards

Learn about faculty members from UT Austin's College of Natural Sciences who have been awarded CAREER Awards from the National Science Foundation.

Headshots of 7 faculty members

Research

Can Dogs Take Bite Out of Neighborhood Crime?

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Features

Layla Parast Aims to Improve Healthcare Using Biostatistics

Layla Parast

UTexas News

Layla Parast Aims to Improve Healthcare Using Biostatistics

Meet new statistics and data science professor, Layla Parast, whose work in biostatistics aims to improve medical treatments and trial outcomes.

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