School of Data Science Welcomes Eleven New Faculty in 2022
The School of Data Science continues to grow and welcomed eleven new faculty this year to their teaching and research teams. They bring with them years of experience in areas such as AI, biostatistics, data science, data system design, data visualization, machine learning, market structures, sports analytics, and statistical mechanics.
Peter Alonzi
Assistant Professor of Data Science
Peter Alonzi’s areas of research include particle physics and the intersection of mental health and the criminal justice system. He previously served as lead of research computing at the School of Data Science and has taught various courses at the University of Virginia since 2005.
Fun Fact: “I coach a rugby team. I am from Chicago. Did you know the fine structure constant is roughly the inverse of 137?"
Yue Cheng
Assistant Professor of Data Science
Assistant Professor of Computer Science
Yue Cheng holds dual appointments with the School of Data Science and Department of Computer Science. His current research focuses on designing efficient data systems for data science. Specifically, he is currently working on: (1) designing efficient stateful serverless computing systems using a full-stack approach spanning applications, platforms, and operating systems/hardware, and (2) building better computing and storage systems for distributed machine learning.
Fun Fact: "I was a Hokie and now I am a Cavalier. I'd be happy no matter whether Hokies win or Cavaliers win when they meet again on the basketball court or football field."
Alex Gates
Assistant Professor of Data Science
Alex Gates is a computational social scientist with an avid curiosity for understanding how connectivity shapes human behavior. Gates also embraces multi-modal communication channels, including award-winning data visualizations, journal covers, interactive web-based models, and videos. Examples of his work include exploring the interdisciplinary structure of a major scientific journal and a video on the collaboration network emerging from one of the NSF's largest gender equity efforts.
Fun Fact: "I love to sail and even built my own sailboat."
Gianluca Guadagni
Associate Professor of Data Science
Gianluca Guadagni has introduced active learning methodologies in applied math courses, and has developed a teaching method course for undergraduate teaching assistants in collaboration with the Center for Teaching Excellence. His research is in statistical mechanics, renormalization group, Stochastic processes, and mathematical modeling. He is interested in understanding complex systems and their many dimensions and components. Recent research works are on derivative-free training of neural networks and on the Stochastic Wave Equation with non-linearity.
Fun Fact: As a kid, I wanted to be a Formula 1 driver, so this job is kind of plan B. I've also flown more than 100 times roundtrip to Europe.
Terence Johnson
Assistant Professor of Data Science
Terence Johnson studies how the structure of markets shapes inefficiencies that hamper economic performance, particularly in developing countries. He uses tools from game theory, mechanism design, and machine learning to measure the impact of market failures, and then design and test new solutions. His projects have ranged from reducing monopoly power in the market for sanitation through auctions in Senegal to empowering female entrepreneurs through mentorship and grants in Kenya to measuring the cost of corruption in public procurement in Tanzania.
Fun Fact: “I adopted a stray dog when I lived in Indiana. I am now fairly certain she is actually a coyote.”
Natalie Kupperman
Assistant Professor of Data Science
Natalie Kupperman is an applied sports science researcher and certified athletic trainer. She studies the use of biometrics, wearables, and other athlete monitoring methods to reduce injury risk and optimize athletic performance. In combination with teaching, Kupperman’s research interests include data infrastructure and pipelines for collaboration in athlete monitoring, dynamic models of injury risk and athlete readiness, and creating seamless monitoring environments for sports teams.
Fun Fact: “Growing up on a farm in North Dakota, I drove a tractor before I could drive a car. I also have an English bulldog named Bodie.”
Sheng Li
Assistant Professor of Data Science
Sheng Li is an artificial intelligence researcher and his long-term goal is to develop intelligent systems in open and dynamic environments. His research interests include trustworthy representation learning (e.g., robustness, fairness, causality, transferability), visual intelligence, user modeling, natural language understanding, bioinformatics, and biomedical informatics. Li also directs the Reasoning and Knowledge Discovery Laboratory.
Fun Fact: "I play Chinese drum since I was three. And I like watching Cocomelon with my son."
Phong Nguyen
Assistant Professor of Data Science
Phong Nguyen is a data scientist and mechanical engineer. His research interest is at the intersection of mechanical engineering and data science in which novel data-driven methods are proposed to solve engineering problems. His main areas of research include physics-informed machine learning, deep generative modeling, uncertainty quantification and robust design optimization, all for the application in materials and structure design.
Fun Fact: “I have been always living in or nearby the capital city of a country. I was born in Hanoi, the capital city of Vietnam, earned my Ph.D. in Seoul, the capital city of Korea, and now live in Virginia, which is very near the capital of the United States.”
Paul Perrin
Professor of Data Science
Professor of Psychology
Paul Perrin holds dual appointments with the School of Data Science and the Department of Psychology. He uses a combination of data science, modern analytic techniques, and community-based participatory research approaches to identify sources of—and potential solutions to—health and disability disparities. His research area include: (a) cultural, familial, and international approaches to disability rehabilitation and adjustment, particularly in medically underserved and minority populations with neurological conditions; (b) social determinants of health (e.g., stigma, access to integrated care and telehealth, personal and collective strengths); and (c) social justice approaches to understand and dismantle oppression.
Fun Fact: "I have a life goal of always having been to a greater number of countries than I am years old. I'm still a few ahead!"
Thomas Stewart
Associate Professor of Data Science
Thomas Stewart is a data scientist specializing in biostatistics, clinical trials, and clinical research education. He serves as lead statistician for two NIH-funded, multi-site clinical trials: Pass It On investigates convalescent plasma as a treatment for patients hospitalized with COVID19, and ACTIV-6 is a platform trial investigating repurposed medications like Ivermectin, Fluvoxamine, and Fluticasone for mild to moderate COVID19.
Fun Fact: “I am a 4th generation Nevadan.”
Wajih Ul Hassan
Assistant Professor of Data Science
Assistant Professor of Computer Science
Wajih Ul Hassan holds a dual appointment as an assistant professor in the School of Data Science and in the Department of Computer Science. His research focuses on securing complex networked systems by leveraging data provenance approaches and scalable system design. He has collaborated with NEC Labs and Symantec Research Labs to integrate his defensive techniques into commercial security products. He received a Symantec Research Labs Graduate Fellowship, a Young Researcher in Heidelberg Laureate Forum, an RSA Security Scholarship, a Mavis Future Faculty Fellowship, a Sohaib and Sara Abbasi Fellowship, and an ACM SIGSOFT Distinguished Paper Award.
Fun Fact: “I can play squash.”