Artificial Intelligence
As artificial intelligence transforms our world, UT Austin is navigating the dynamic intersection of technology and society with strategic focus. Our commitment to advancing AI catapults us to the forefront of global advancements, reaching beyond the Forty Acres to revolutionize education, address the most pressing needs of society and redefine the boundaries of possibility.
At UT, AI is more than a field of study; it is a force driving creative collaborations, groundbreaking research and the development of future leaders poised to navigate the ever-evolving landscape.
If you are seeking expertise on other subjects, please call University Media Relations at 512-471-3151 or consult our general Media Experts Guide.
Robotics
Joydeep Biswas
Associate Professor
, Department of Computer Science
, College of Natural Sciences
, joydeepb@cs.utexas.edu
Joydeep Biswas' research areas include perception, planning, and failure recovery for autonomous mobile robots. These topics support his goal of having autonomous service mobile robots deployed on a campus to city scale, both indoors and outdoors, in real world human environments, performing assistive tasks accurately and robustly on demand, over deployments spanning years. He is most interested in tackling research problems that will directly improve long-term autonomy on real world robots deployed in human environments. Prior to joining UT Austin, Joydeep was an Assistant Professor in the College of Information and Computer Sciences at University of Massachusetts Amherst. He earned his PhD in Robotics from Carnegie Mellon University in 2014, and his B.Tech in Engineering Physics from the Indian Institute of Technology Bombay in 2008.
Media Contact: Christine Sinatra, christine.sinatra@austin.utexas.edu, 512-471-4641
Peter H Stone
Professor
, Department of Computer Science
, College of Natural Sciences
+1 512 471 9796, pstone@cs.utexas.edu
Peter Stone is the founder and director of the Learning Agents Research Group (LARG) within the Artificial Intelligence Laboratory in the Department of Computer Science at The University of Texas at Austin, as well as associate department chair and Director of Texas Robotics. He was a co-founder of Cogitai, Inc. and is now Executive Director of Sony AI America.
His main research interest in AI is understanding how we can best create complete intelligent agents. He considers adaptation, interaction, and embodiment to be essential capabilities of such agents. He focuses mainly on machine learning, multiagent systems, and robotics. He researches topics that are inspired by challenging real-world problems. His AI applications have included robot soccer, autonomous bidding agents, autonomous vehicles, and human-interactive agents.
Media Contact: Christine Sinatra, christine.sinatra@austin.utexas.edu, 512-471-4641
Yuke Zhu
Associate Professor
, Department of Computer Science
, College of Natural Sciences
, yukez@cs.utexas.edu
Dr. Yuke Zhu is a leading mind in robot vision and learning. Dr. Zhu received his masters and PhD from Stanford University. His doctoral thesis centers around closing the perception-action loop to make robot intelligence more generalized and applicable to less-controlled environments. As an undergraduate, he received dual degrees from Zhejiang University and Simon Fraser University. Dr. Zhus publications have won several awards and nominations, and his work has been covered by media outlets, such as MIT Technology Review and Stanford News. In addition, hes had research collaborations with Snap Research, Allen Institute for Artificial Intelligence, and DeepMind Technologies.
He writes: "My goal is to build intelligent algorithms for robots and embodied agents that reason about and interact with the real world. My research lies at the intersection of robotics, computer vision, and machine learning. I focus on developing methods and principles of perception and decision making to realize general-purpose robot autonomy in the wild."
Media Contact: Christine Sinatra, christine.sinatra@austin.utexas.edu, 512-471-4641
Machine Learning
Swarat Chaudhuri
Professor
, Department of Computer Science
, College of Natural Sciences
, swarat@cs.utexas.edu
Dr. Swarat Chaudhuri works in the intersection of formal methods and artificial intelligence (AI). He received his bachelor of technology in computer science from the Indian Institute of Technology Kharagpur. He completed a doctorate in philosophy in computer science at the University of Pennsylvania. Dr. Chaudhuri was previously a faculty member at Pennsylvania State University and Rice University, has taught a wide range of undergraduate and graduate courses on computer science, and has a long track record of federally funded research. His accolades include an NSF CAREER award, a Google Research Award, the ACM SIGPLAN John Reynolds Doctorate Dissertation Award, and multiple distinguished paper awards.
His research vision is to build a new generation of AI systems that are designed from the ground up with the goals of reliability, transparency, and security. He seeks to realize this vision through a synthesis of ideas from programming languages, formal methods, and machine learning.
He is a member of UT Austin's Programming Languages and Formal Methods group, a core faculty member in UT's Machine Learning Laboratory, and an affiliate of Texas Robotics.
Media Contact: Christine Sinatra, christine.sinatra@austin.utexas.edu, 512-471-4641
Kristen L Grauman
Professor
, Department of Computer Science
, College of Natural Sciences
+1 512 471 9521, grauman@cs.utexas.edu
Kristen Grauman is a Full Professor in the Department of Computer Science where she leads the UT Computer Vision Group. Her research is in computer vision and machine learning. She is a Fellow of AAAI, an Alfred P. Sloan Research Fellow, and a recipient of the Presidential Early Career Award for Scientists and Engineers, the 2013 Computers and Thought Award, and several best paper awards. Prof. Grauman serves as Associate Editor-in-Chief for the IEEE Transactions on Pattern Analysis and Machine Intelligence. She was elected to the Academy of Distinguished Teachers in 2017, and received her B.A. from Boston College and her Ph.D. from MIT.
Media Contact: Christine Sinatra, christine.sinatra@austin.utexas.edu, 512-471-4641
Adam R Klivans
Professor
, Department of Computer Science
, College of Natural Sciences
+1 512 471 9790, klivans@cs.utexas.edu
Adam Klivans is Director of the NSF AI Institute for Foundations of Machine Learning and the Machine Learning Laboratory. His research interests lie in machine learning and theoretical computer science, in particular, Learning Theory, Computational Complexity, Pseudorandomness, Limit Theorems, and Gaussian Space.
Media Contact: Christine Sinatra, christine.sinatra@austin.utexas.edu, 512-471-4641
Risto P Miikkulainen
Professor
, Department of Computer Science
, College of Natural Sciences
+1 512 471 7316, +1 512 471 9571, risto@cs.utexas.edu
Risto Miikkulainen is a Professor of Computer Science at the University of Texas at Austin and AVP of Evolutionary Intelligence at Cognizant Technology Solutions. He received an M.S. in Engineering from the Helsinki University of Technology (now Aalto University) in 1986, and a Ph.D. in Computer Science from UCLA in 1990. His current research focuses on methods and applications of neuroevolution, as well as neural network models of natural language processing and vision, subdisciplines within artificial intelligence. He is an author of over 380 articles in these research areas.
Media Contact: Christine Sinatra, christine.sinatra@austin.utexas.edu, 512-471-4641
Public Policy & Ethics
Sherri R Greenberg
Professor of Practice
, Lyndon B Johnson School of Public Affairs
+1 512 471 8324, +1 512 656 6592, srgreenberg@austin.utexas.edu
Sherri Greenberg served for 10 years as a member of the Texas House of Representatives, completing her final term in January 2001. In 1999, she was appointed by the Speaker of the House to chair the House Pensions and Investments Committee, which oversees the Texas State Employee Retirement System, state employee health insurance program, Teacher Retirement System, local public employee retirement systems, and regulation of state investments and public securities. After the 1999 legislative session, the Speaker appointed her as chair of the Select Committee on Teacher Health Insurance.
Greenberg served two terms on the House Appropriations Committee, which is the House's budget writing committee, and served on the Appropriations Committee's Education and Major Information Systems Subcommittees. Other committee assignments included the House Economic Development Committee and the Welfare-to-Work Committee.
Greenberg's professional background is in public finance. She served as the Manager of Capital Finance for the City of Austin from 1985 to 1989, overseeing the City's debt management, capital budgeting, and capital improvement programs. Prior to that she worked as a Public Finance Officer for Standard & Poor's Corporation in New York, where she analyzed and assigned bond ratings to public projects across the country.
Greenberg has a B.A. in Government from UT Austin and an M.S. in Public Administration and Policy from the London School of Economics. At the LBJ School she teaches courses in public financial management, policy development, and public administration and management. Her teaching and research interests include public finance and budgeting, Texas state government, local government, health care, education, utilities, transportation, and campaigns and elections.
Media Contact: Paul Corliss, paul.corliss@austin.utexas.edu,
Transportation
Chandra R Bhat
Professor
, Fariborz Maseeh Department of Civil, Architectural and Environmental Engineering
+1 512 471 4535, bhat@mail.utexas.edu
Good Systems Executive Team Member
Joe J. King Endowed Chair in Engineering, Civil, Architectural, and Environmental Engineering
Cockrell School of Engineering
Areas of Expertise:
- Automation
- Emerging mobility technologies: AVs, EVs, connected vehicles, micromobility
- AI and transportation safety and equity
- E-commerce impacts on land-use and travel demand
Human-Computer Interaction
Justin W Hart
Assistant Professor of Practice
, Department of Computer Science
, College of Natural Sciences
, hart@cs.utexas.edu
Hart is an assistant professor of practice with the College of Natural Sciences and a postdoctoral fellow affiliated with the Building-Wide Intelligence Project and the Learning Agents Research Group under the supervision of professor Peter Stone in the Department of Computer Science. Hart teaches the Autonomous Robots stream of the Freshman Research Initiative and supervises the UT Austin Villa @ Home RoboCup@Home team. Currently Hart is working on semantic mapping, autonomous human-robot interaction, and artificial intelligence representations and architectures for service robots. He received his M.S., M.Phil, and Ph.D. from Yale University, his M.Eng from Cornell University, and his B.S. from West Virginia University.
He writes: "In particular, I am interested in themes in which we model human intelligence, leverage knowledge of human behavior, or take inspiration from human behavior. Additionally, I am interested in themes which I believe are likely to shape the direction of robotics and move robots into homes, workspaces, and public places, such as service robots. The dual goals of my research are to better understand human intelligence and to push the fields of artificial intelligence and robotics towards widespread robotic deployments that impact our everyday lives."
Media Contact: Christine Sinatra, christine.sinatra@austin.utexas.edu, 512-471-4641
Keri K Stephens
Professor
, Department of Communication Studies
, Moody College of Communication
+1 512 471 0554, keristephens@austin.utexas.edu
Dr. Keri Stephens is an expert in using technology to communicate during infrastructure-related crises and disasters and in the workplace. She has authored over 100 articles/book chapters, and her two most recent books are the national-level-award winning book New Media in Times of Crisis (2019, Routledge), and the two-time national-level award-winning book Negotiating Control: Organizations and Mobile Communication (2018, Oxford University Press).
Her research has received federal (e.g., NSF), state, industry, and international agency (e.g., Japan Science & Technology Agency) support. Her team recently authored the Texas Water Development Boards Flood Resource Guide for Community Officials in 2022, and they developed the Public Involvement Training for TxDOT in 2023. She is currently working on the Digital Risk Infrastructure Program (DRIP) for under-resourced Texas Communities.
She is a Professor in Organizational Communication Technology and is Co-Director of Technology, Information, & Policy Institute in the Moody College of Communication at The University of Texas at Austin. She has a BS in biochemistry from Texas A&M University, an MA and Ph.D. from The University of Texas at Austin, is a flood survivor (1978 Flood on the Clearfork of the Brazos River in Texas) and grew up in the rural Texas community of South Bend, TX.
Media Contact: Kathleen Mabley, kmabley@austin.utexas.edu, 512-232-1417
Craig Watkins
Professor
, School of Journalism and Media
, Moody College of Communication
+1 512 471 4071, +1 512 471 6676, craig.watkins@austin.utexas.edu
S. Craig Watkins is the Ernest A. Sharpe Centennial Professor and the Executive Director of the IC² Institute at the University of Texas at Austin. His research focuses on the technical, social, and ethical implications of artificial intelligence. His research explores the challenges of deploying AI in the context of high stakes contexts like health care. For example, he was part of a multidisciplinary team of social scientists, psychologists, and computer scientists who prototyped a chatbot to support parents dealing with postpartum depression. Watkins is part of an NIH-funded project that is exploring the design of ethical AI to address the crisis of rising rates of suicide among youth, especially Black youth. His team is also probing an NIH dataset to understand how social determinants of health influence health outcomes and health disparities. Through his leadership at the IC2 Institute, Watkins is collaborating with the Dell Medical School and UT faculty to enhance the use of artificial intelligence to address health disparities.
Craig is an internationally recognized expert in media and technology systems and the author of six books and numerous articles and book chapters. His research explores, among other things, how technological innovation built the hip-hop economy (Hip Hop Matters), the social and behavioral implications of young peoples engagement with computer-mediated technologies (The Young and the Digital), the shifting contours of the digital divide (The Digital Edge), and the creative ways young people adopt technology to navigate a precarious society and economy (Dont Knock the Hustle). This work illuminates the nuanced ways in which structural inequalities influence the design, deployment, and adoption of computer-mediated systems leading to both systemic challenges and opportunities to enhance the human experience.
Watkins work has been profiled in places as varied as the Washington Post, The Atlantic, Newsweek, TIME, ESPN, and NPR, and featured at venues like SXSW, The Aspen Institute, The Boston Federal Reserve, New York Hall of Science, MITs Media Lab, The New York Times Dialogue on Race, and the Brene Brown podcast, Unlocking Us.
Media Contact: Kathleen Mabley, kmabley@austin.utexas.edu, 512-232-1417
Space
Niall Gaffney
Director for Data Intensive Computing
, Texas Advanced Computing Center
+1 512 475 9504, ngaffney@tacc.utexas.edu
Niall Gaffney's background primarily revolves around the management and utilization of large inhomogeneous scientific datasets. Niall, who earned his B.A., M.A., and Ph.D. degrees in astronomy from The University of Texas at Austin, joined TACC in May 2013. Most of his focus has been on creating environments to foster better data practices from improving metadata, data processing, analysis, and reuse. He focuses on improving researchers' data practices to accelerate outcomes and better feed the Machine Learning and Artificial Intelligence applications which are becoming more broadly adopted in science and engineering research fields. Much of this stems from his 13 years as designer and developer for the archives at the Space Telescope Science Institute (STScI), which holds the data from the Hubble Space Telescope, Kepler, and James Webb Space Telescope missions. He was also a leader in developing the Hubble Legacy Archive. This project harvested the 20+ years of Hubble Space Telescope data to create some of the most sensitive astronomical data products available for open research. Before his work at STScI, Niall was worked as "the friend of the telescope" for the Hobby Eberly Telescope (HET) project at the McDonald Observatory in west Texas. This was the start of his work in planning experiments and then cataloging the data the HET produced.
Media Contact: Laura Klopfenstein, klopfenstein@mail.utexas.edu, 512-921-2650
Stella S Offner
Professor
, Department of Astronomy
, College of Natural Sciences
+1 512 471 3853, soffner@astro.as.utexas.edu
Prof. Offner's research focuses on understanding how stars like the Sun form by combining numerical simulations, observations and observational modeling. She is also interested in applying statistical techniques and machine learning to parse data and identify the physical characteristics of forming stars. She is a core faculty member in the Oden Institute for Computational Engineering and Science (specifically the Center for Scientific Machine Learning), and a member of the Center for Planetary Systems Habitability and the Machine Learning Laboratory.
Prof. Offner received her bachelor's degrees in physics and mathematics from Wellesley College in 2003 and completed a Ph.D. in physics at the University of California at Berkeley in 2009. From 2009-2012 she was an NSF Astronomy & Astrophysics prize postdoctoral fellow at the Harvard-Smithsonian Center for Astrophysics and a NASA Hubble prize postdoctoral fellow at Yale from 2012-2014. Before joining the astronomy faculty at UT Austin in 2017, she was an assistant professor at the University of Massachusetts Amherst.
Media Contact: Christine Sinatra, christine.sinatra@austin.utexas.edu, 512-471-4641
For more information, contact: University Communications, Office of the President, 512-471-3151.
