Biography
Volodymyr M. Minin, Ph.D., is Professor of Statistics in the School of Information & Computer Sciences at the University of California, Irvine. Minin received his Ph.D. in Biomathematics from the University of California, Los Angeles in 2007. He spent 10 years on faculty of the University of Washington, Seattle before joining UC Irvine in 2017. Minin's research focuses on developing statistical methods for infectious disease dynamics, with applications ranging from tuberculosis transmission in Botswana to SARS-CoV-2 surveillance using wastewater data. His other research interests include phylogenetics, population genetics, and systems biology.
Return to topEducation
- Ph.D. in Biomathematics, University of California, Los Angeles, 2007
- M.S. in Biomathematics, University of California, Los Angeles, 2004
- M.S. in Mathematics, University of Idaho, 2002
- B.S. in Mathematics, Odesa National University, 2000
Distinctions
- Fellow of the American Statistical Association, 2026
- Savage Award in Applied Methodology, International Society for Bayesian Analysis, 2008
Areas of Expertise
- Infectious Disease Dynamics
- Statistical Forecasting
- Bayesian Statistics
- Statistical Phylogenetics
- Systems Biology
Recent Publications
- Sebastian JN, Minin VM, “Gaussian process priors with Markov properties for effective reproduction number inference” (opens in new tab), Journal of the Royal Statistical Society Series A: Statistics in Society, pp. qnag088, 2026.
- Němcová B, Goldstein IH, Sebastian J, Minin VM, Bracher J, “Unjustified Poisson assumptions lead to overconfident estimates of the effective reproductive number” (opens in new tab), Epidemiology & Infection, vol. 154, pp. e79, 2026.
- Medina CM, Palacios JA, Minin VM, “Accounting for reporting delays in real-time phylodynamic analyses with preferential sampling” (opens in new tab), PLoS Computational Biology, vol. 21, pp. e1012970, 2025.
- Goldstein HI, Parker DM, Jiang S, Minin VM, “Semiparametric inference of effective reproduction number dynamics from wastewater pathogen surveillance data” (opens in new tab), Biometrics, vol. 80, pp. ujae074, 2024.
- Bayer D, Goldstein I, Fintzi J, Lumbard K, Ricotta E, Warner S, Busch LM, Strich JR, Chertow DS, Parker DM, Boden-Albala B, Dratch A, Chhuon R, Quick N, Zahn M, Minin VM, “Semi-parametric modeling of SARS-CoV-2 transmission using tests, cases, deaths, and seroprevalence data” (opens in new tab), Annals of Applied Statistics, vol. 18, pp. 2307–2325, 2024.
- Goldstein HI, Jon Wakefield, Minin VM, “Incorporating testing volume into estimation of effective reproduction number dynamics” (opens in new tab), Journal of the Royal Statistical Society Series A: Statistics in Society, vol. 187, pp. 436–453, 2024.
- Magee AF, Karcher MD, Matsen FA, Minin VM, “How trustworthy is your tree? Bayesian phylogenetic effective sample size through the lens of Monte Carlo error” (opens in new tab), Bayesian Analysis, vol. 19, pp. 565—593, 2024.
- Awasthi N, Minin VM, Huang J, Chow D, Xu J, “Fitting a stochastic model of intensive care occupancy to noisy hospitalization time series” (opens in new tab), Statistics in Medicine, vol. 42, pp. 5189–5206, 2023.
- Tang M, Dudas G, Bedford T, Minin VN, “Fitting stochastic epidemic models to gene genealogies using linear noise approximation” (opens in new tab), Annals of Applied Statistics, vol. 17, pp. 1–22, 2023.
- Fintzi J, Wakefield J, Minin VN, “A linear noise approximation for stochastic epidemic models fit to partially observed incidence counts” (opens in new tab), Biometrics, vol. 78, pp. 1530–1541, 2022.
Contact Information
Website: https://vnminin.github.io
Email: vminin@uci.edu
Address: 2068 Bren Hall
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Last updated on 11/9/2026.