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School of Data Science welcomes 9 new faculty in 2025
The University of Virginia’s School of Data Science is excited to welcome nine new faculty in Fall 2025. Their expertise and research priorities cross all four of the School's data science domains and nearly all of the 10 areas of research practice. Read below for an introduction to each new member of the School and where their research interests lie.
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YY Ahn
Quantitative Foundation Distinguished Professor of Data Science
Yong-Yeol (YY) Ahn is a Quantitative Foundation Distinguished Professor at the University of Virginia School of Data Science. He was previously a professor at the Indiana University School of Informatics, Computing, and Engineering (2011–2025) and a visiting professor at MIT (2020–2021). He worked as a postdoctoral research associate at the Center for Complex Network Research at Northeastern University and as a visiting researcher at the Center for Cancer Systems Biology at Dana-Farber Cancer Institute.
His research focuses on data science, spanning methodological work in network science, machine learning, and AI, as well as their applications to computational social science, computational neuroscience and biology, and the science of science. He is a recipient of several awards, including a Microsoft Research Faculty Fellowship and the LinkedIn Economic Graph Challenge.
Fun Fact: "I was once invited to a gastronomy conference co-organized by Ferran Adrià. I think the conference had more tasting sessions than talks."
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Hannah Bako
Assistant Professor of Data Science
Hannah Bako is a researcher exploring how to inspire and support creativity in data visualization design.
Her work sits at the intersection of data visualization, human-computer interaction, and design, combining empirical studies with tool development to investigate how people conceptualize and implement design ideas. She examines how designers work with code, interact with examples, and engage with AI-powered systems. Using these insights, she creates tools that enable expressive, context-aware, and diverse visualizations. Her research bridges foundational studies of visualization behavior with practical systems that enhance the design process and strengthen visual communication.
Fun fact: "Outside of research, I love amigurumi crochet, gardening, and rewatching old sitcoms."
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Peter Beling
Professor of Data Science
School of Data Science Director — National Security Data and Policy Institute
Peter A. Beling focuses on generative AI research as part of UVA’s new National Security Data and Policy Institute. His work centers on resilient, mission-aligned AI, with broader interests in cyber resilience and trusted systems. At the nexus of systems theory and AI, Beling explores large language models, reinforcement learning, and the co-design of algorithms and the systems in which they operate. His research supports a range of national security applications, including mission engineering, test and evaluation, and predictive maintenance.
This is Beling's third stint at UVA. His first time in Charlottesville saw him earn his B.A. in Mathematics. From 1993 to 2021, he held a series of roles at UVA, including professor of Systems Engineering, director of the UVA site of the Center for Visual and Decision Informatics (a National Science Foundation Industry/University Cooperative Research Center), and director of the Adaptive Decision Systems Laboratory.
Fun Fact: “In 1993, as a top-level backgammon player, I accepted a challenge to play for money against a new computer program developed at IBM’s Watson Research Center. To my surprise—and financial regret—the machine crushed me. I had to write a sizable check to its creators. The program was based on a novel approach in reinforcement learning (RL) known as temporal difference learning. My loss helped underscore a startling realization: RL had not only learned to play backgammon—it had surpassed the expertise developed by humans in two millennia of gameplay. Remarkably, this level of success wouldn’t be seen again in other complex games until over two decades later, when deep reinforcement learning burst onto the scene in 2015.”
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Jordan Bryan
Assistant Professor of Data Science
Jordan Bryan is a statistician with broad expertise in multivariate data analysis. He has studied and developed statistical methods in the fields of environmental monitoring, high-energy physics, and cancer genomics. His research interests include Bayesian statistics, robust estimation, and information-assisted hypothesis testing.
Prior to joining the faculty at UVA, he was a postdoctoral researcher at the University of North Carolina at Chapel Hill, where he was supported by training grants from the National Institute of Environmental Health Sciences (NIEHS) and the National Heart Lung and Blood Institute (NHLBI). He also worked as an associate computational biologist at the Broad Institute of MIT and Harvard. As of January 2024, he is the Secretary of the junior section of the International Society for Bayesian Analysis.
Fun Fact: "In addition to being a member of various statistical associations, I am also a member of the North American Dostoevsky Society, and I'm looking forward to attending their XIX symposium in 2026."
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Tyler Cody
Research Associate Professor of Data Science
Tyler Cody is a research associate professor of data science at the University of Virginia School of Data Science, working with the National Security Data and Policy Institute. He is a systems theorist and machine learning researcher, with research interests in developing and applying systems theory to bridge systems engineering and artificial intelligence.
Cody uses abstract systems theory as a meta-theory for learning in order to study phenomena of interest in general learning processes. His research is applied to machine prognostics, telecommunications, computer networks, fraud detection, and computer vision, among other areas, following themes of change and reuse, lifecycles, and iterated games.
Fun Fact: "For fun, I play tennis, ski, and play guitar."
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Daniel Graham
Associate Professor of Data Science
Daniel Graham joins the School of Data Science after previously serving as an associate professor in the UVA Department of Computer Science. His research and teaching focus on the intersection of data science, cybersecurity, and software engineering, with particular interests in penetration testing, network security, and the practical applications of machine learning to cyber defense.
A double Hoo, Graham has authored multiple widely read books, including an international bestseller on ethical hacking and the second edition of Metasploit, published by No Starch Press. His teaching experience spans large-scale undergraduate courses of 400+ students as well as advanced classes in security and mobile app development.
In addition to his academic work, Graham has industry experience at Microsoft and continues to collaborate with organizations on applied cybersecurity challenges.
Fun Fact: "I planted two apple trees this summer."
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Lei Li
Assistant Professor of Data Science
Lei Li's research interests are in computer vision and computer graphics, with a focus on advancing machine spatial intelligence to perceive, understand, and interact with the 3D world by developing innovative machine learning techniques combined with geometric principles.
Lei’s work has been published in top-tier venues, including CVPR, ICCV, ECCV, NeurIPS, and IEEE TVCG, covering topics including 3D scene reconstruction, human-scene interaction, shape analysis, geometric transfer learning, and generative models. He has served on technical program committees for major conferences including Eurographics and Pacific Graphics.
Before joining UVA in 2025, Lei worked as a postdoctoral researcher at the Technical University of Munich in Germany and École Polytechnique / Inria in France.
Fun Fact: "I am into digital collectible card games when not researching."
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Karsten Siller
Associate Professor of Data Science
Karsten Siller's academic interests span developmental and cell biology, image analysis, high-throughput data pipelines, and high-performance computing. He joined UVA in 2013 as an Assistant Professor in the Department of Biology within the College of Arts & Sciences. Before his current appointment at the School of Data Science, he served as Associate Director for Research Computing User Services. In that role, he led a team of computational scientists and oversaw technical support operations, workshop portfolio, collaborative research initiatives, and community outreach.
He has deep expertise in image processing and image analysis and is a strong advocate for open-source software development and interactive, project-based teaching. His research focuses on building reproducible and resilient, scalable data analysis workflows that are portable across diverse computing environments. He is also interested in developing intuitive user interfaces for composing modular, multi-stage pipelines, with integrated visualization tools that are both user-friendly and extensible.
Fun Fact: "I am an outdoor enthusiast. A few years ago, I was introduced to ultra trail running and have been hooked ever since."
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Stephen Turner
Associate Professor of Data Science
Assistant Dean for Research
Stephen Turner serves as an Associate Professor of Data Science and the Assistant Dean for Research at the School of Data Science. His work bridges genomics, data science, and national security, with a focus on biosecurity, synthetic biology, conservation, and bioinformatics applications in human health.
Turner began his academic career as a faculty member in the UVA School of Medicine Department of Public Health Sciences, where he served from 2011 to 2019. During that time, he was founding director of the UVA Bioinformatics Core and collaborated on many NIH-funded research programs, mentored students across disciplines, and taught several biomedical data science graduate courses and workshops.
After leaving UVA, Turner worked as a consultant for federal agencies on biosecurity and national security initiatives, before joining a biotech startup, leading computational biology and genomics strategy for species de-extinction and conservation efforts, integrating large-scale sequencing, genome editing, and machine learning technologies.
A trusted advisor to multiple biotech startups, Turner brings deep experience at the interface of academia, industry, entrepreneurship, government, and policy. His research interests span the application of novel computational approaches to problems in biosecurity, biodiversity conservation, and human health.
Fun Fact: "I once briefed a room full of special forces and policy officials about how resurrecting a woolly mammoth isn’t a national security threat (…probably). Never thought I’d discuss 'Pleistocene ecosystem restoration' and 'existential biorisk' in the same breath."
