Cody Carroll

Cody Carroll is an assistant professor with joint appointments in the Department of Mathematics and Statistics and the Master's in Data Science and Artificial Intelligence program (MS-DSAI).

Cody started his path in education as an ESL teacher in Nishinomiya, Japan. Since then he has taught statistics, math, and data science at UC Davis before coming to USF.

In his work as an applied statistician and data scientist, he develops and applies statistical tools for complex and multimodal functional and longitudinal data. Much of his work applies these methods to fields where they are increasingly needed, including conservation, citizen science, and clinical medicine.

He describes most of his collaborative work as translation, finding clear ways to communicate results across the gap between statisticians and other scientists. He has collaborated with conservationists at The Nature Conservancy, auditory researchers at St. Jude and UC San Diego, ophthalmologists at Stanford Medicine, and scientists at California's Office of Environmental Health Hazard Assessment, among others.

• Time warping & curve registration
• Multivariate functional data
• Statistical consulting
• Communication through statistics

• Functional and longitudinal data analysis
• Conservation, citizen science, and wildlife
• Statistical modeling of healthcare data
• Growth, development, and aging across the lifespan

• Director, Leveraging Data for Environmental and Social Impact (LEDESI) Initiative, Data Institute, USF (2025-present)
• Co-Lead, Data Institute + CRASE Research Support Initiative, USF (2023-present)
• Member, Student Research and Creative Activity Advisory Council, College of Arts and Sciences, USF (2025-present)
• Math/MSDSAI Liaison for Strategic Enrollment Management Events, USF (2024-present); Co-Host, The USF Data Science Podcast (2022-present)

• UC Davis, PhD in Statistics, 2021
• UC Davis, MS in Statistics, 2017
• UT Austin, BS in Mathematics, 2014

• Lecturer in Statistics, University of California, Davis (2022)
• Data Scientist, Wells Fargo (2021-2022)
• ESL Teacher, Nishinomiya Imazu Senior High School, Japan (2014-2015)

• Early Career Researcher Award, International Society for Ecological Modeling Global Conference, 2025
• CRASE Interdisciplinary Action Group Grant, University of San Francisco, 2026
• Centennial Innovation Fund Award, University of San Francisco, 2025
• Peter Hall Research Award, Department of Statistics, UC Davis, 2021

• Wolfson, P. & Carroll, C. (2026). A Longitudinal Analysis of the Clinical Practice of Ketamine-Assisted Psychotherapy with Adolescents and Young Adults. Frontiers in Psychiatry, 17.

• Bernstein, R., Waterman, S., Klausmeyer, K., Murphy, N., Rohde, M.M., & Carroll, C. (2026). Improving Conservation Efficiency: Accelerating Groundwater Sustainability Plan Reviews Using Large Language Models. Environmental Challenges. 

• Erra, A., Miller, C., Chen, J., et al., Carroll, C., & Manor, U. (2026). An Open-Source Deep Learning-Based Toolbox for Automated Auditory Brainstem Response Analyses (ABRA). Scientific Reports. 

• Carroll, C., Furrow, R.E., & Gerhart, L.M. (2025). Consistency and Validity of Participatory Science Data: A Comparison of Seasonality Patterns of Northern California and Nevada Birds across eBird and iNaturalist. Citizen Science: Theory and Practice, 10(1). 

• Carroll, C. & Müller, H.-G. (2023). Latent Deformation Models for Multivariate Functional Data and Time Warping Separability. Biometrics, 79(4), 3345-3358.

• Carroll, C., Müller, H. G., & Kneip, A. (2020). Cross‐component registration for multivariate functional data, with application to growth curves. Biometrics, 77(3), 839-851.

• Huey, R. B., Carroll, C., Salisbury, R., & Wang, J. L. (2020). Mountaineers on Mount Everest: effects of age, sex, experience, and crowding on rates of success and death. PLoS One, 15(8), e0236919.

• Carroll, C., Bhattacharjee, S., Chen, Y., et al. (2020). Time dynamics of COVID-19. Scientific reports, 10(1), 1-14.

• Carroll, C., Gajardo, A., Chen, Y., et al. (2020). fdapace: Functional data analysis and empirical dynamics. R package version 0.5, 5.