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Our faculty are world-renowned for contributions to statistical theory, methodology, and application with ongoing research collaborations from the UK to Sweden to Korea to Chile. Award winning instruction serves 5,800+ students per year with over 60 new courses developed since 2007.

 

 

TENURE/TENURE TRACK FACULTY

Kate Calder

Dr. Catherine (Kate) Calder 
Email: calder@austin.utexas.edu 
Professor
, Chair 
Department of Statistics and Data Sciences 
Website 
Ph.D. in Statistics, Duke University, 2003 

Catherine (Kate) Calder joined the Statistics and Data Sciences faculty in 2019 and currently serves as department chair. Previously, she spent 16 years on the faculty of The Ohio State University. She served as an associate director (2015–2018) and co-director (2018–2019) of the Mathematical Biosciences Institute, an NSF Division of Mathematical Sciences Research Institute located on the Ohio State campus. She is currently an associate editor for the Annals of Applied Statistics and Bayesian Analysis and has served the profession through various elected roles in sections of the American Statistical Association (ASA) and in the International Society for Bayesian Analysis. Her research has been funded by the NIH, NSF, NASA, and other agencies and foundations. She received the ASA Section on Statistics and the Environment’s 2013 Young Investigator Award and was elected Fellow of the ASA in 2014. Dr. Calder's current research focuses on spatio-temporal statistics, Bayesian methods, and network analysis. Her work is motivated by applications in the environmental, social, and health sciences. 

 

 

carvalho

Dr. Carlos Carvalho 
Email: carlos.carvalho@mccombs.utexas.edu 
La Quinta Centennial Professor
Department of Statistics and Data Sciences
Department of Information, Risk, and Operations Management
Executive Director, Salem Center for Policy
Website 
Ph.D. in Statistics, Duke University, 2006 

La Quinta Centennial Professor in Business Carlos M. Carvalho joined The University of Texas at Austin in 2010. Previously he was on the faculty at the University of Chicago Booth School of Business. His research focuses on Bayesian statistics in complex, high-dimensional problems with applications ranging from finance to genetics. Some of his current projects include work on large-scale factor models, graphical models, Bayesian model selection, particle filtering and stochastic volatility models. Dr. Carvalho is also a professor of statistics at McCombs, as well as the Executive Director of the Salem Center for Policy. 

 


Damien PaulDr. Paul Damien 
Email: paul.damien@mccombs.utexas.edu 
Professor 
Department of Information, Risk, and Operations Management 
Department of Statistics and Data Sciences 
Website 
Ph.D. in Mathematics, Imperial College, London, 1995 

Paul Damien joined The University of Texas at Austin in 2004, prior to which he was at the University of Michigan Ross School of Business. Dr. Damien is the B.M. Rankin Jr. Professor of Business in the Department of Information, Risk, and Operations Management, Red McCombs School of Busines. His research interests lie at the intersection of mathematics, Bayesian statistics, and applications in business, engineering, and stochastic optimization. He is a Fellow of the Royal Statistical Society of England. He is twice recipient of the United Kingdom Engineering and Physical Sciences Research Council Research Award, and was awarded the United Kingdom Overseas Visiting Fellowship by the Royal Statistical Society of England. He has been a Visiting Scholar at the Department of Economics in the University of Groningen, Netherlands. He consults for several companies in a variety of industries world-wide. 

 


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Dr. Nhat Ho
Email: minhnhat@utexas.edu 
Assistant Professor
Department of Statistics and Data Sciences
Website 
Ph.D. in Statistics, University of Michigan, 2017 

Nhat Ho joined The University of Texas at Austin in 2020 as an Assistant Professor. Previously, he was a postdoctoral fellow in the Electrical Engineering and Computer Science Department at the University of California, Berkeley, under Professor Michael I. Jordan, and Professor Martin J. Wainwright. His current research focuses on the interplay of four principles of statistics and data sciences. They include heterogeneity of data, interpretability of models, stability, and scalability of optimization and sampling algorithms. 

 

 

Linero Tony

Dr. Antonio (Tony) Linero 
Email: antonio.linero@austin.utexas.edu 
Assistant Professor 
Department of Statistics and Data Sciences 
Website 
Ph.D. in Statistics, University of Florida, 2015 

Antonio (Tony) Linero joined The University of Texas at Austin faculty in 2019. Before joining UT Austin, he was an Assistant Professor in the Department of Statistics at Florida State University. He is a member of the International Society for Bayesian Analysis and the American Statistical Association. He serves as associate editor for Biometrics. In 2015, Dr. Linero received the Laplace award from the Section on Bayesian Statistical Science of the American Statistical Association. His research has been supported by the National Science Foundation and through work with the Science of Test Research Consortium. His research focuses on developing flexible and appropriate Bayesian methods for complex longitudinal data, as well as developing model selection and variable selection tools within the Bayesian nonparametric framework for high dimensional problems. His work also pursues Bayesian nonparametrics for missing data and causal inference problems in which analysts are forced to (i) confront the curse of dimensionality when estimating low-dimensional effects of interest, and (ii) are required to make in-principle unverifiable assumptions. 

 


meyersDr. Lauren Ancel Meyers  Email: laurenmeyers@austin.utexas.edu 
Professor 
Department of Integrative Biology (IB) 
Department of Statistics and Data Sciences 
Website 
Ph.D. in Biological Sciences, Stanford University, 2000 

Dr. Lauren Ancel Meyers joined the faculty at The University of Texas at Austin in 2003 where she currently is the Cooley Centennial Professor of Integrative Biology and Statistics and Data Sciences. She has been a member of the external faculty of the Santa Fe Institute since 2003 and now serves on its Scientific Advisory Board. She leads an interdisciplinary team of scientists, engineers, and public health experts in uncovering the social and biological drivers of epidemics and building practical tools for the CDC and other global health agencies to track and mitigate emerging viral threats, including COVID-19, pandemic influenza, Ebola, HIV, and Zika. Her research has been published in over 100 peer-reviewed articles in major journals and covered by the popular press, including The Wall Street Journal, New York Times, Washington Post, NPR, CNN, and the BBC. Professor Meyers was named as one of the top 100 global innovators under age 35 by the MIT Technology Review in 2004 and received the Joseph Lieberman Award for Significant Contributions to Science in 2017.

 

 

Mueller Peter

Dr. Peter Mueller (Müller)
Email: pmueller@math.utexas.edu 
Professor 
Department of Statistics and Data Sciences 
Department of Mathematics 

Website 
Ph.D. in Statistics, Purdue University, 1991 

Peter Mueller (Müller) joined The University of Texas at Austin faculty in 2011 sharing joint appointments in the Department of Statistics and Data Sciences and the Department of Mathematics. He is a member of the Oden Institute for Engineering and Computational Sciences and adjunct professor in the Department of Information, Risk, and Operations Management, Red McCombs School of Business. He is an adjunct professor of Biostatistics at M.D. Anderson Cancer Center. Before coming to Austin, he served on the faculty in the Institute of Statistics and Decision Science at Duke University and in the Department of Biostatistics at M.D. Anderson Cancer Center. He is an elected fellow of the International Society of Bayesian Analysis (ISBA), the American Statistical Association (ASA), and the Institute of Mathematical Statistics (IMS), and has been awarded the Zellner Medal (ISBA). He has served as elected president of the International Society of Bayesian Analysis (ISBA) and chair of the Section on Bayesian Statistical Science of the ASA (ASA/SBSS). Mueller has authored more than 210 scientific publications, 10 books and edited volumes and has served on the editorial board of three scientific journals and technical series.

 


Murray JaredDr. Jared S. Murray 
Email: jared.murray@mccombs.utexas.edu 
Assistant Professor

Department of Information, Risk, and Operations Management
Department of Statistics and Data Sciences
Website
Ph.D. in Statistical Science, Duke University, December 2013

Jared S. Murray joined The University of Texas at Austin in 2017 as an Assistant Professor. He was previously a visiting assistant professor in the Department of Statistics at Carnegie Mellon University. His current research interests are in developing flexible Bayesian multivariate models for heterogenous and structured data, with applications to multiple imputation for missing data, latent variable modeling, and causal inference. He was recently awarded an NSF grant, “Improving Probabilistic Record Linkage and Subsequent Inference,” to develop new methods for matching records across files in the absence of unique identifiers, and for making inference using the combined files. 

 

 

vagheesh sds web

Dr. Vagheesh M. Narasimhan
Email: vagheesh@utexas.edu 
Assistant Professor 
Department of Integrative Biology (IB) 
Department of Statistics and Data Sciences (SDS) 
Department of Population Health 
Website
Ph.D. in Mathematical Genomics & Medicine, University of Cambridge, 2017 

Vagheesh M. Narasimhan joined The University of Texas at Austin in 2020. Previously, he was a post-doctoral fellow in the Department of Genetics at Harvard Medical School. He is broadly interested in problems at the intersection of genomics, computer science and statistics. In particular, his lab works to develop scalable and efficient methods to make sense of complex, large-scale datasets that are being generated in the fields of human genetics and medical imaging. The goal is to leverage these new methodologies to understand the genetic basis of disease as well as to address questions related to human evolution. 

 


Sager thomasDr. Thomas (Tom) Sager
Email: tomsager@mail.utexas.edu 
Professor 

Department of Information, Risk, and Operations Management 
Department of Statistics and Data Sciences 
Website 
Ph.D. in Statistics, University of Iowa, 1973 

Thomas (Tom) Sager joined The University of Texas at Austin in 1978. His research focuses on the development and application of econometric models to study the empirical behavior of insurance companies. The models involve simultaneously interacting manifest and latent variables interacting in autocorrelated nonlinear panel data structures. He has applied these to the prediction of insurer insolvency, the risks of mortgage-backed securities, the effects of the Affordable Care Act, the assessment of global systemic risk, consequences of regulation, and other issues. He seeks to illuminate how agency theory, transactions cost economics, theories of limited and unlimited risk, and other ideas play out to explain insurers’ management of their enterprise risks. 

 


Sarkar AbhraDr. Abhra Sarkar
Email: abhra.sarkar@utexas.edu 
Assistant Professor 
Department of Statistics and Data Sciences 
Website 
Ph.D. in Statistics, Texas A&M University, 2014 

Abhra Sarkar joined The University of Texas at Austin faculty in 2017 as an Assistant Professor. Prior to that, he was a postdoctoral research associate at Duke University. His research interests center around the development of novel statistical approaches that aid in the study of complex real-world phenomena and provide new insights into related scientific queries while also having much broader general utility. These problems arise in diverse application areas, including especially in nutritional epidemiology, auditory, and vocal communication neuroscience. Dr. Sarkar is a 2018 recipient of the Mitchell Prize, and his work has been funded by the NSF, NIH, and ASA, among others.

 

 

Sarkar Purna

Dr. Purnamrita (Purna) Sarkar
Email: purna.sarkar@austin.utexas.edu 
Assistant Professor 
Department of Statistics and Data Sciences 
Website 
Ph.D. in Statistics, Carnegie Mellon University, 2010 

Purnamrita (Purna) Sarkar joined The University of Texas at Austin in 2014 as an Assistant Professor. Previously, she was a postdoctoral scholar at the University of California, Berkeley, jointly in the Department of Electrical Engineering and Computer Sciences and the Department of Statistics. She works on large-scale statistical machine learning problems with a focus on statistical models, asymptotic theory, and scalable inference algorithms for large networks. Along with investigators across campus, Sarkar co-leads the NSF TRIPODS (Transdisciplinary Research in Principles of Data Science) grant to establish a new institute on the Foundations of Data Science at UT Austin.

 

 

Scott JamesDr. James G. Scott
Email: james.scott@mccombs.utexas.edu 
Professor 
Website 
Department of Statistics and Data Sciences 
Department of Information, Risk, and Operations Management 
Ph.D. in Statistics, Duke University, 2009 

James G. Scott joined The University of Texas at Austin in 2009. His research focuses on statistical methodology for high-dimensional data sets, with applications in a diverse set of areas spanning the social, physical, and biomedical sciences. Three areas of methodological focus include (1) large-scale multiple testing, anomaly-detection and screening problems, where the rate of false discoveries must be controlled in order to yield viable inferences; (2) inference in sparse models; and (3) the application of data-augmentation theory and algorithms to improve the efficiency of Bayesian inference in large-scale models for discrete data sets. His recent applied work has included collaborations in health care, demography, linguistics, biology, and neuroscience. He is the associate editor for The Annals of Applied Statistics and Journal of Computational and Graphical Statistics. He received the UT System Regents’ Outstanding Teaching Award in 2014. 

 

 
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Dr. Thomas (Tom) Shively 
Email: tom.shively@mccombs.utexas.edu 
Professor 
Department of Information, Risk, and Operations Management 
Website 
Ph.D. in Statistics, University of Chicago, 1986 

Thomas (Tom) Shively joined The University of Texas at Austin in 1986. He is a past president of the Austin chapter of the American Statistical Association and a past chair of the Business and Economics sections of the American Statistical Association. He is four-time recipient of the Outstanding Professor Award in the Full-Time and Executive MBA Programs and also three-time recipient of the Joe D. Beasley Award for Teaching Excellence in the MBA program. His research focuses on nonparametric function estimation and its application in energy economics, finance, marketing, and transportation science. 

 

 

Walker SDr. Stephen G. Walker 
Email: s.g.walker@math.utexas.edu 
Professor 

Department of Statistics and Data Sciences
Department of Mathematics 
Website 
Ph.D. in Statistics, Imperial College, 1995 

Stephen G. Walker joined The University of Texas at Austin in 2013, having previously held positions at the University of Kent, Bath, and Imperial College, in the UK. He is currently executive editor for Journal of Statistical Planning and Inference, and associate editor for Journal of the American Statistical Association, having previously been associate editor for Scandinavian Journal of Statistics, Statistica Sinica, and Annals of Statistics. He has received an EPSRC Advanced Research Fellowship, 2001–2006, and has been funded by the NSF. Dr. Walker's research is predominately in Bayesian methods, including nonparametric, asymptotics, computational and methodological and foundational. Other areas of interest include hypothesis testing, inequalities, matrix, and linear algebra.

 

 

Williamson SineadDr. Sinead Williamson
Email: sinead@austin.utexas.edu 
Assistant Professor 

Department of Statistics and Data Sciences
Website
 
Ph.D. in Engineering (Machine Learning), University of Cambridge, 2012 

Sinead Williamson joined The University of Texas at Austin in 2013. She was a Senior Research Scientist with Amazon, Inc. and a Lead Machine Learning Scientist with CognitiveScale. Her main research focus is the development of nonparametric Bayesian methods for machine learning applications. In particular, she is interested in constructing distributions over correlated measures and complex structures, in order to model structured data sets or data with spatio-temporal dependence. Examples include models for documents whose topical composition varies through time, and models for temporally evolving social networks. A key research goal is the development of efficient inference algorithms for such models, and she is currently investigating methods that allow us to apply Bayesian nonparametric techniques to large datasets. She has worked as a Senior Research Scientist with Amazon, Inc. and a Lead Machine Learning Scientist with CognitiveScale, and is on the Board of Directors of Women in Machine Learning. 

 


Zhou MingyuanDr. Mingyuan Zhou Email: mingyuan.zhou@mccombs.utexas.edu 
Associate Professor 
Department of Information, Risk, and Operations Management 
Department of Statistics and Data Sciences 
Website 
Ph.D. in Electrical and Computer Engineering, Duke University, 2013 

Mingyuan Zhou joined The University of Texas at Austin faculty in 2013 as an Assistant Professor. He has served as the 2018–2019 treasurer of the Bayesian Nonparametrics Section of the International Society for Bayesian Analysis and as area chairs for leading machine learning conferences, including NeurIPS 2017-2020, ICLR 2019 and 2021, and AAAI 2020 and 2021. Dr. Zhou’s research lies at the intersection of Bayesian statistics and machine learning. His research interests include statistical theory and methods, generative models, deep learning, reinforcement learning, statistical inference for big data, and Bayesian nonparametrics. His work currently focuses on advancing both statistical inference with deep learning and deep learning with probabilistic methods

 


Dr. Corwin (Cory) ZiglerZigler Cory 
Email: cory.zigler@austin.utexas.edu 
Associate Professor 
Department of Statistics and Data Sciences 
Department of Women's Health
Website 
Ph.D. in Biostatistics, UCLA, 2010 

Corwin (Cory) Zigler joined the faculty of The University of Texas at Austin in 2018, sharing joint appointments in the Department of Statistics and Data Sciences and the Department of Women’s Health at Dell Medical School. Prior to joining UT, he was faculty in the Department of Biostatistics at the Harvard T.H. Chan School of Public Health. He currently serves as associate editor for the journals Biometrics and Biostatistics, and is heavily involved through elected positions in the Health Policy Statistics Section of the American Statistical Association. He has received research funding from NIH, EPA, and the Health Effects Institute, and his career awards include the 2010 Carolbeth Korn Prize for the most outstanding graduating student in the UCLA School of Public Health, a 2012 Young Investigator Award from the Statistics in Epidemiology Section of the American Statistical Association, and the 2019 Rothman Prize for the best paper published in Epidemiology. Dr. Zigler's research is motivated by problems in public health and epidemiology. Specific areas of statistical methods development include methods for causal inference with interference, intermediate variables (mediation analysis, principal stratification), confounding in high dimensions, model uncertainty/model averaging, treatment effect heterogeneity, spatial statistics, missing data, environmental health data science, and tools for transparent/reproducible research. 

 

 

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INSTRUCTIONAL FACULTY

 

Blondeau Lauren

Dr. Lauren Blondeau
Email: lauren.blondeau@utexas.edu
Assistant Professor of Instruction
Ph.D. in Educational Psychology, The University of Texas at Austin, 2014

Lauren Blondeau joined the Department of Statistics and Data Sciences in the Spring of 2015 and currently serves as an Assistant Professor of Instruction. She has won three Faculty and Staff Appreciation Awards from Services for Students with Disabilities (Spring 2016, Fall 2016, Spring 2018). Additionally, she has obtained two professional development awards; one from the Department of Statistics and Data Sciences (Spring 2017) and one from the Department of Undergraduate Studies (Fall 2019). She is a member of the Faculty Advisory Committee for the Services for Students with Disabilities (2019–2020; 2020–2021).

 

 

Collins Sarah

Dr. Sarah Collins
Email: smcollins@utexas.edu
Assistant Professor of Instruction
Ph.D. in Educational Psychology, The University of Texas at Austin, 2010

Sarah Collins joined the Department of Statistics and Data Sciences in 2010. Dr. Collins also teaches courses in Statistics and Program Evaluation for the Department of Educational Psychology. In addition, she serves as a statistical consultant for non-profit organizations around Austin. 

 

 

 

Dr. Kristin Harvey
 Kristin Harvey
Email: kharvey@utexas.edu 
Director of Undergraduate Studies 
Associate Professor of Instruction

Ph.D. in Educational Psychology, The University of Texas at Austin, 2013

Kristin Harvey joined the Department of Statistics and Data Sciences in the fall of 2013 and currently serves as the Director of Undergraduate Studies. She coordinates two large introductory statistics courses: Elementary Statistical Methods and Data Analysis for the Health Sciences. Her teaching awards include the President’s Associates Teaching Excellence Award (2019), the Dads’ Association Centennial Teaching Fellowship (2018), and a College of Natural Sciences teaching award (2016). Her work on course transformation, course creation, and materials development projects has been funded by the College of Natural Sciences and the Center for Teaching and Learning. She is an elected member of Faculty Council and serves on the Faculty Council Executive Committee and as Chair of the Educational Policy Committee (2020–2021). 

 

 

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Dr. Matthew Hersh
Email: matt.hersh@austin.utexas.edu
Assistant Professor of Instruction
Ph.D. in Statistics, The University of Kentucky, 2007

Matthew Hersh joined the Department of Statistics in 2007. As part of SDS’s Graduate Fellows Program, Dr. Hersh assisted graduate students in analyzing data, preparing the results, and presenting conclusions for faculty members around campus. 

 

 

 

 
Hong KyongJooDr. KyongJoo Hong
Email: kjhong@utexas.edu
Assistant Professor of Instruction 

Ph.D. in Educational Psychology, The University of Texas at Austin, 2017 



KyongJoo Hong joined the Department of Statistics and Data Sciences in 2018. She is currently working on several research papers primarily focusing on two areas: the impacts of father involvement on maternal marital satisfaction and children’s behavior problems, and the effects of parents’ acculturation attitudes on adolescents’ outcomes. She is interested in the holistic support of college students, focusing on students' intellectual, emotional, social, and spiritual well-being collectively. 

 


Parker MaryDr. Mary Parker

Email: parker@math.utexas.edu
Associate Professor of Instruction

Ph.D. in Statistics, The University of Texas at Austin, 1988

Mary Parker has been teaching for the Department of Mathematics at The University of Texas at Austin since 1989, and joined the Department of Statistics and Data Sciences in 2007. She is also active in the statistics education communities of the American Statistical Association, the Mathematical Association of America, and the Consortium for the Advancement of Undergraduate Statistics Education (CAUSE).

 


Ragsdale SallySally Ragsdale
Email: sally.ragsdale@austin.utexas.edu
Associate Professor of Instruction
M.S. in Statistics, The University of Texas at Austin, 2012

Sally Ragsdale joined the Department of Statistics and Data Sciences in the summer of 2012 and currently serves as the course coordinator for SDS 328M Biostatistics and the undergraduate certificate program coordinator. Her teaching awards include the College of Natural Sciences Foundation Advisory Council Teaching Endowment Award (2018), the Natural Sciences Council Faculty Service Award (2015), and the College of Natural Sciences New Employee Excellence Award (2014). Her work on course transformations and the development of an online statistics platform has been funded by the Center for Teaching and Learning and the Center for the Skills and Experience Flags. She currently serves on the Quantitative Reasoning Flag Committee as well as the College of Natural Sciences Non-Tenure-Track Faculty Committee, where she is co-chair of the Faculty Climate Sub-Committee. 

 

 
noprofilepicDr. Lindsey Smith
Email: lwolff@utexas.edu
Associate Professor of Instruction
Ph.D. in Educational Psychology, The University of Texas at Austin, 2012

Lindsey Smith joined the Department of Statistics and Data Sciences in 2012. Her primary research focus has been on the evaluation of multilevel models, specifically its use with multiple membership data structures. She has been a course coordinator for two courses and, among others, currently serves on the College of Natural Sciences Non-Tenure Track Faculty Committee and Policy and Guidelines Subcommittee.

 

 

 

 

 

Dr. Bindu ViswanathanViswanathan Bindu
Email: bindu@austin.utexas.edu
Assistant Professor of Instruction
Ph.D. in Biostatistics, Emory University, 1999

Bindu Viswanathan joined the Department of Statistics and Data Sciences in Fall 2011. She currently serves as the graduate advisor for the MS in Statistics program and as director of the portfolio programs in Applied Statistical Modeling and Scientific Computation. She previously served as Industry Liaison for the department. 

 

 

 

Woodward NathanielDr. Nathaniel Woodward
Email: nathaniel.raley@utexas.edu
Assistant Professor of Instruction
Ph.D. in Educational Psychology, The University of Texas at Austin, 2018

Nathaniel Woodward is a graduate of the Department of Statistics and Data Sciences (M.S. Statistics, 2016) who joined the department in 2017 as a Graduate Statistical Consultant. He served as an Assistant Instructor the same year and became a full-time faculty member in 2018.

 

 

 

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LECTURERS

 

noprofilepicDr. Layla Guyot
Lecturer
Email: layla.guyot@austin.utexas.edu
 
 

 

 

 

 

 

 

Myers MaggieDr. Maggie Myers
Lecturer
Email: myers@cs.utexas.edu

 

 

 

 

 

 

 

 

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ADJUNCT FACULTY


Lingham RamaDr. Rama Lingham
Adjunct Associate Professor
Email: rlingham@utexas.edu

 

 

 

 

 

 

 

 

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