Meet New Faculty In the College of Natural Sciences

Junyeong Ahn, Assistant Professor, Physics

Junyeong Ahn is a theoretical physicist who studies how electrons organize themselves in ways that give rise to surprising properties in materials. He is particularly interested in uncovering new principles that enable materials to conduct electricity or interact with light in unexpected fashions. His recent work examines the hidden “shapes” and “twists” of electronic wave functions—subtle quantum features that influence material properties. Ahn received his Ph.D. in Physics from Seoul National University and completed postdoctoral training at the University of Tokyo, RIKEN and Harvard University.

Brian Don, Assistant Professor, Human Development and Family Sciences

Brian Don is a social-health psychologist who studies intimate relationships and families. His research examines how relationships can thrive and how they contribute to the mental and physical wellness of the individuals involved. His work focuses on: the role of positive emotions and interactions in long-term relationship and family functioning; the transition to parenthood and its effects on couples; the use of meditation and mindfulness as tools for transforming relationships; and how people seek and provide social support in close relationships. Don previously served as a lecturer at the University of Auckland, and he received his Ph.D. from Kent State University. He completed postdoctoral fellowships at the University of North Carolina at Chapel Hill and the University of California, San Francisco.

Elias Stengel-Eskin, Assistant Professor, Computer Science

Elias Stengel-Eskin’s research spans artificial intelligence, natural language processing and computational linguistics, with a focus on developing AI agents that can intelligently communicate and collaborate with people and each other. This includes work on multi-agent communication and collaboration, converting language to action, grounding language to vision and handling uncertainty, ambiguity and underspecification. Before joining UT Austin, he conducted postdoctoral research at the University of North Carolina at Chapel Hill. He received his Ph.D. from Johns Hopkins University and undergraduate degrees from McGill University.

Brandon Yushan Feng, Assistant Professor, Computer Science

Brandon Yushan Feng’s research focuses on leveraging machine learning for vision, imaging and graphics applications, including as it pertains to bioimaging, astronomical discovery making and 3D motion magnification. He previously conducted postdoctoral research in the MIT Computer Science and Artificial Intelligence Laboratory. Feng received his Ph.D. from the University of Maryland, College Park and his M.S. and B.A. degrees from the University of Virginia.

Sebastian Gomez, Assistant Professor, Astronomy

Sebastian Gomez is an astrophysicist who specializes in observations of cosmic explosions such as supernovae and black holes destroying stars. Using telescopes in space and on the ground, he aims to understand how stars live, die and shape their surroundings. Before joining UT Austin, he was a Clay Postdoctoral Fellow at the Harvard–Smithsonian Center for Astrophysics and a postdoctoral fellow at the Space Telescope Science Institute, where he supported the development of NASA’s Nancy Grace Roman Space Telescope. Gomez earned his Ph.D. from Harvard University, studying rare supernovae and tidal disruption events, and his undergraduate degree from The University of Texas at El Paso, near his hometown of Ciudad Juárez, Mexico.

ChangHoon Hahn, Assistant Professor, Astronomy

ChangHoon Hahn develops and applies machine learning methods to study cosmology and galaxy evolution. His research addresses questions about the nature of dark energy, the sum of neutrino masses and how dark matter environments influence the evolution of galaxies. He has been involved in the ongoing Dark Energy Spectroscopic Instrument (DESI) survey, including as co-chair of its Bright Galaxy Survey Working Group, and the Subaru Prime Focus Spectrograph (PFS) survey, for which he served as co-leader in the PFS Cosmology Survey. He has directed a variety of collaborations developing state-of-the-art cosmological simulations and testing galaxy formation models. Before joining UT Austin, Hahn was an assistant professor at the University of Arizona and an assistant astronomer for the Steward Observatory. He previously held positions as a research scholar at Princeton University and as a postdoctoral fellow at Lawrence Berkeley National Laboratory and the University of California, Berkeley Center for Cosmological Physics. He earned his Ph.D. from New York University and his B.S. from Rutgers.

Volkan Isler, Professor, Computer Science

Volkan Isler studies fundamental problems that arise in robotics, sensing and networks (RSN) tasks and builds RSN systems, focusing on robotics for environmental monitoring, agricultural automation and home automation. He is especially interested in perception-action coupling and networked robotics, and much of his work involves designing planning algorithms and perceptual representations that incorporate sensing, communication and actuation constraints. Isler came to UT after serving for more than 16 years on the faculty at the University of Minnesota. From 2021 to 2023, he was head of Samsung’s AI Center in New York, and he co-founded Farm Vision Technologies to bring pre-harvest yield mapping technologies to growers. He received his Ph.D. from the University of Pennsylvania and his B.S. from Boğaziçi University in Turkey.

Dima Kozakov, Professor, Molecular Biosciences

Dima Kozakov develops computational tools that integrate physics, AI and biology to transform drug design and improve understanding of disease mechanisms. Software he developed is widely used by pharmaceutical companies worldwide, particularly in cancer therapeutics. Jointly appointed in UT’s Oden Institute for Computational Engineering and Sciences as the W.A. “Tex” Moncrief, Jr. Chair in Computational Life Sciences and Biology, Kozakov is launching a new research center focused on using artificial intelligence and deep learning to model molecular interactions and predict therapeutic effects in cancer research, with support from the Cancer Prevention and Research Institute of Texas (CPRIT). He was named a Clarivate Highly Cited Researcher in 2024, and his CLUSPRO web server is consistently ranked among the top tools for modeling biomolecular interactions, serving more than 40,000 academic users globally. He joined UT after serving on the faculty at Stony Brook University. He received his master’s in applied mathematics and physics from the Moscow Institute of Physics and Technology and his Ph.D. in biomedical engineering from Boston University.

William Kretschmer, Assistant Professor, Computer Science

William Kretschmer researches quantum computational complexity theory, with a focus on the limitations of quantum algorithms and the interplay between classical and quantum computational techniques. Topics of his work include query complexity, structural complexity, pseudorandom quantum states, learning theory and the stabilizer formalism. He earned his Ph.D. from UT Austin and B.S. degrees from MIT. Before returning to UT Austin, Kretschmer was a postdoctoral fellow specializing in quantum at the Simons Institute for the Theory of Computing at the University of California, Berkeley. 

Suzana Gonçalves Leles, Assistant Professor, Marine Science

Suzana Gonçalves Leles is an oceanographer with a background in microbial ecology. Her research focuses on the diverse lifestyles of marine microbes, as well as their distribution and impact on ecosystem functioning. She uses models and data to study the ecological niches and biogeography of protists and how these microbes influence nutrient cycling at regional and global scales. Her work addresses both ecological and evolutionary responses of microbial communities to a rapidly changing ocean. By combining theory, numerical modeling, and empirical data, she investigates fine-scale cellular processes that shape ecosystems and drive large-scale biogeochemical patterns. She conducted postdoctoral research at the University of Southern California, including as a Simons Foundation Postdoctoral Fellow. She earned her Ph.D. from Swansea University in the United Kingdom and her bachelor’s and master’s degrees from Federal University of Rio de Janeiro in Brazil. 

Jia Leo Li, Associate Professor, Physics

Jia Leo Li is a condensed matter experimentalist specializing in low-temperature electronic systems in low-dimensional materials. His research focuses on emergent quantum phenomena in 2D materials and their van der Waals structures. Before joining UT Austin, he was an associate professor of physics at Brown University. His work has been recognized with a Sloan Research Fellowship, a National Science Foundation CAREER Award and Brown University’s Salamon Faculty Award for scholarly excellence. Li received his Ph.D. from Northwestern University and conducted postdoctoral research at Columbia University.

Michael Marty, Associate Professor, Chemistry

Michael Marty’s research focuses on understanding how lipids and proteins interact within cell membranes to uncover novel forms of biological regulation. Combining analytical chemistry, biochemistry and bio-nanotechnology, he develops new methods to study these complex systems using lipoprotein nanodiscs and mass spectrometry. He served on the faculty at the University of Arizona from 2016 until joining UT’s Department of Chemistry this year. He is the recipient of multiple awards including a National Science Foundation CAREER Award, the American Chemical Society Division of Analytical Chemistry Arthur F. Findeis Award for Achievements by a Young Analytical Scientist and the American Society for Mass Spectrometry Ron Hites Award. Marty earned his B.A. degrees at St. Olaf College, completed his Ph.D. in chemistry at the University of Illinois Urbana-Champaign and conducted postdoctoral research at the University of Oxford. 

Yang Ni, Associate Professor, Statistics and Data Sciences

Yang Ni works at the intersection of statistics, artificial intelligence, biology and health. His research develops statistical methods for causal discovery, Bayesian model-based clustering and reinforcement learning, with applications to multi-omics and electronic health records. He was previously an associate professor at Texas A&M University, where he received the Research Impact Award and the Faculty Excellence Award. At Texas A&M, he co-directed the Cancer Prevention and Research Institute of Texas-funded Single Cell Data Science Core and the Center for Statistical Bioinformatics. Ni currently serves as an associate editor for the Journal of the American Statistical Association, Bayesian Analysis and The American Statistician. He was a postdoctoral fellow at UT Austin and earned his Ph.D. from Rice University.

Pratik Patil, Assistant Professor, Statistics and Data Sciences

Pratik Patil’s research develops mathematical foundations for modern machine learning and artificial intelligence. Because many of today’s most powerful models are extremely large and complex, behaving in surprising ways that classical statistical wisdom cannot easily explain, Patil builds theory to understand these behaviors and to provide scientists and engineers with practical tools for designing more efficient and reliable systems. Some of his past research has studied why very large models can sometimes perform well on new data despite overfitting; how combining many models into ensembles can improve accuracy; and how strategies like selective use of data or features can make models more efficient and stable. He has also developed new approaches to evaluate and compare models so practitioners can make confident choices about model size, training and tuning. Patil completed postdoctoral research at the University of California, Berkeley and received his Ph.D. from Carnegie Mellon University, master’s degrees from the University of Toronto and a bachelor’s degree from the Indian Institute of Technology.

Shelley Sianta, Assistant Professor, Integrative Biology

Shelley Sianta is an evolutionary ecologist and geneticist whose research focuses on plant adaptation and speciation. She combines field and greenhouse experiments with population genomics and phylogenomics to study how plants adapt to harsh environments, diverge into new species and exchange genetic material through introgression. She conducted her postdoctoral research at the University of Minnesota, and received her Ph.D. from the University of California, Santa Cruz and her B.S. from Colorado State University.

Leah Whigham, Professor, Nutritional Sciences

Leah Whigham is an obesity scientist whose work bridges research, clinical care and community health. Leveraging her expertise to ensure that community needs drive priorities informed by science, she connects basic and translational research for practical impact. Prior to coming to UT, she was on the faculty at The University of Texas, El Paso and served as the founding executive director of the Paso del Norte Institute for Healthy Living. Whigham’s research has increased understanding of metabolism as it relates to obesity, the influence of nutrients and immune function on body composition, the impact of the environment on health, the development of software tools for healthcare providers, the use of economic development strategies to increase access to healthy food and the application of multi-sector system models to drive change at a population level. She received her Ph.D. from the University of Wisconsin–Madison, where she also did postdoctoral research, and her B.S. from Iowa State University.