After hiring 15 new faculty members in its first year, the School of Data Science and Society (SDSS) at the University of North Carolina at Chapel Hill has hired an additional 16 faculty members. Some faculty members have a joint or secondary appointment with another department or school, and some have a 100% appointment in SDSS.
“We’re thrilled to welcome this second cohort of faculty,” said Stan Ahalt, dean of the School of Data Science and Society. “We recruited talented researchers and educators who work at the intersection of AI and health as well as hired jointly with three additional disciplines: communication, sociology, and maternal fetal medicine. Data science is a team science and a team sport, and I’m excited about our growing group of faculty.”
David Adalsteinsson, professor and director of undergraduate studies
David Adalsteinsson is a professor with joint appointments in the School of Data Science and Society and the Department of Mathematics in the College of Arts & Sciences. He holds a Ph.D. in mathematics from the University of California, Berkeley and was a postdoctoral scholar at the Lawrence Berkeley National Lab. He has been a faculty member at UNC-Chapel Hill since July 1999. His research interests include biology, interface problems, spatial modeling, algorithm development, and creating tools for scientific computing and visualization. Adalsteinsson is also the founder of Visual Data Tools and the director of undergraduate studies for the School of Data Science and Society.
Wai-Tong (Louis) Fan, associate professor
Louis Fan will join the School of Data Science and Society in January 2025 as an associate professor. He comes to SDSS from Indiana University, where he served as an associate professor in the mathematics department. Additionally, he is a research associate in the Department of Organismic and Evolutionary Biology at Harvard University. Fan’s research focuses on rigorous analysis, design, and application of data-oriented stochastic models to deepen our understanding of complex natural phenomena, particularly in biology, health science, and atmospheric science. His work emphasizes practical applications to genomics and systems biology, exploring their implications for cancer dynamics, virus co-infection spread, and human health.
Melissa Haendel, professor; director of precision health and translational informatics and the Sarah Graham Kenan Distinguished Professor, Department of Genetics, UNC School of Medicine
Melissa Haendel is the director of precision Health and translational informatics and the Sarah Graham Kenan Distinguished Professor at the Department of Genetics in the UNC School of Medicine. She also has a secondary appointment at SDSS. She co-founded the Monarch Initiative and the National Covid Cohort Collaborative. Her background is in molecular genetics, developmental biology, and translational informatics, focusing on open science and semantic engineering. Haendel’s vision is to weave together health care systems, basic science research, and patient-generated data by developing data integration technologies and innovative data capture strategies. Haendel’s research has focused on integrating genotype-phenotype data to improve rare disease diagnosis and mechanism discovery. She also leads and participates in international standards organizations to support improved data sharing and utility worldwide.
Sun-ha Hong, associate professor
Sun-ha Hong will join UNC-Chapel Hill in July 2025 as an associate professor with joint appointments in the Department of Communication in the College of Arts & Sciences and the School of Data Science and Society. Hong’s research examines social and historical patterns of uncertainty, doubt, belief and disbelief around AI and data-driven technologies. His work critiques the politics of knowledge, visibility, and power relations across areas like state surveillance and other predictive and anticipatory systems, smart machines, self-tracking, biohacking, and Silicon Valley technoculture. Hong was previously a faculty member at Simon Fraser University, Canada, and a postdoctoral scholar at the Massachusetts Institute of Technology. He is the author of “Technologies of Speculation: The Limits of Knowledge in a Data-Driven Society” (NYU Press, 2020) and is working on his second book, “Predictions Without Futures.”
Lauren Kucirka, assistant professor
Lauren Kucirka is joining the faculty in the Department of Obstetrics and Gynecology, division of maternal-fetal medicine in the School of Medicine, with a secondary appointment in the School of Data Science and Society. Kucirka is a practicing maternal-fetal medicine physician and a Ph.D.-trained epidemiologist with more than 15 years of experience designing and conducting large data studies to inform clinical practice.
Steve Marron, professor, School of Data Science and Society; Amos Hawley Distinguished Professor of Statistics and Operations Research
J. S. (Steve) Marron is the Amos Hawley Distinguished Professor of Statistics and Operations Research and has a joint appointment in the School of Data Science and Society. He is also a professor in the Department of Biostatistics in the Gillings School of Global Public Health and an adjunct professor in the Department of Computer Science in the College of Arts & Sciences. His research lies in many areas of statistics, data science, and machine learning, with a particular emphasis on gaining simultaneous insights from diverse data types, including genomics, genetics, imaging, and demographics. In novel data analyses, he enjoys using deep concepts from diverse mathematical areas, including geometry and topology.
Julie McMurry, professor of the practice
Julie McMurry is a professor of the practice in the School of Data Science and Society and has a secondary appointment in the Department of Genetics in the School of Medicine. She is also the Translational and Integrative Sciences Lab’s associate director and chief operating officer. The lab leverages semantic technologies to enhance rare disease diagnosis, accelerate scientific breakthroughs, and improve health care delivery. McMurry is passionate about establishing a robust knowledge infrastructure and harmonizing data, which are vital components of the research ecosystem.
Lina Montoya, assistant professor
Lina Montoya is an assistant professor at the School of Data Science and Society and has a secondary appointment in the Department of Biostatistics in the Gillings School of Global Public Health. Her methodological research focuses on questions in causal inference, particularly within precision medicine, motivated by applications in the U.S. criminal legal system and HIV care adherence in sub-Saharan Africa. Through a NIH Pathway to Independence Award and with collaborators Jennifer Skeem and Michael Kosorok, she is developing and implementing novel precision medicine methods to better match services to the characteristics, needs and risk factors of previously incarcerated people with serious mental illness, to reduce criminal recidivism among this population.
Rei Sanchez-Arias, teaching assistant professor and Master of Applied Data Science faculty director
Rei Sanchez-Arias is a teaching assistant professor at SDSS and faculty director for the Master of Applied Data Science (MADS) program. He was most recently an associate professor of data science and assistant chair in the Data Science and Business analytics Department at Florida Polytechnic University. He strives to implement innovative and effective methods for teaching and learning of data science, has been recognized with excellence in teaching awards, and has been an invited speaker at multiple conferences to discuss topics in data science education. In recent research projects, he has focused on applying and developing data mining and statistical learning methods and algorithms to propose solutions to applied sciences and engineering problems.
Jack Snoeyink, professor
Jack Snoeyink is a professor with joint appointments in the Department of Computer Science in the College of Arts & Sciences and the School of Data Science and Society. He works on computational geometry, a branch of computer science theory that designs and analyzes algorithms and data structures for problems best stated in geometric form. His main application areas are terrain modeling in geographic information systems, molecular structure validation and biochemistry improvement, computational topology, computer graphics, and information visualization. In 2015-2018, Snoeyink rotated as a program director at the U.S. National Science Foundation, Computer and Information Science & Engineering (CISE), in the Computing and Communication Foundations (CCF) division. He was one of the four program directors who helped create the Transdisciplinary Research in Principles of Data Science (TRIPODS) program, establishing centers to explore the application of math, statistics, and computer science in foundations and applications in data science.
Justin Sola, assistant professor
Justin Sola is joining UNC-Chapel Hill as an assistant professor with joint appointments in the Department of Sociology in the College of Arts & Sciences and the School of Data Science and Society. He completed his Ph.D. in criminology, law, and society at the University of California, Irvine, emphasizing race and justice. Sola researches gun ownership, trends in social research, and the interaction of inequality with the criminal justice system. He uses preregistered experiments, longitudinal designs, semi-structured interviews, participant observation, and machine learning to assess causal heterogeneity.
David Yokum, professor of the practice
David Yokum joined the School of Data Science and Society as a professor of the practice, in addition to his service as North Carolina’s chief scientist in the Office of State Budget and Management. He was previously director of The Lab @ DC in the D.C. Mayor’s Office and before that, a member of the White House’s social and behavioral sciences team and director of the U.S. Office of Evaluation Sciences. He works with local, state, and federal governments on how to generate and use evidence within policy making, while also pursuing a research agenda on the psychology of how people change their minds and make decisions, especially as related to the interpretation and use of data.
Ran Zhang, assistant professor
Ran Zhang will join the School of Data Science and Society as an assistant professor in July 2025. She received her Ph.D. from Princeton University and is completing her postdoctoral studies at the University of Washington. She is a computational biologist and develops machine learning methods for high-dimensional, sparse, heterogeneous, and multimodal genomics data. She is particularly interested in using network and deep learning-based approaches to characterize human diseases and sex differences from bulk and single-cell data across different technologies, species, and modalities.
Weitong Zhang, assistant professor
Weitong Zhang joined the School of Data Science and Society as an assistant professor in July 2024 after completing his Ph.D. in computer science at the University of California, Los Angeles. His research interests include developing robust and efficient reinforcement learning and other machine learning algorithms, applying cutting-edge machine learning techniques to scientific discoveries, and providing theoretical justifications and confidence for these applications.
Chudi Zhong, assistant professor
Chudi Zhong is joining UNC-Chapel Hill as an assistant professor with joint appointments in the School of Data Science and Society and the Department of Statistics and Operations Research in the College of Arts & Sciences. Zhong received her Ph.D. in computer science from Duke University. Her research lies at the intersection of machine learning, optimization, and human-model interaction. Specifically, she focuses on developing interpretable machine-learning algorithms and pipelines to facilitate high-stakes decision-making.
Tarek Zikry, assistant professor
Tarek Zikry will join the School of Data Science and Society in July 2025 after serving as a postdoctoral research scientist in the Columbia University Statistics Department and Zuckerman Institute. He will also be a faculty member in the Bioinformatics and Computational Biology T32 training program at UNC-Chapel Hill. As a biostatistician, his research interests focus on reinforcement learning for dynamic clinical and public health treatment regimens and manifold learning for studying single-cell behaviors in cancer and neuroscience.
For more information about SDSS faculty, visit the SDSS website at datascience.unc.edu/people.