Hal S. Stern
Provost & Executive Vice Chancellor, University of California, Irvine
Distinguished Professor, Department of Statistics, University of California, Irvine
Biography
Hal S. Stern, Ph.D., is Provost and Executive Vice Chancellor and Distinguished Professor in the Department of Statistics at the University of California, Irvine. Stern received a Ph.D. in Statistics from Stanford University in 1987. His research focuses on Bayesian statistical methods, forensic statistics, and the application of statistical methods to study early-life experiences and their impact on neurodevelopment. He has made contributions to the statistical analysis of forensic evidence, including work on comparative bullet lead analysis, fingerprint examination, and bloodstain pattern analysis, and has served on numerous National Academy of Sciences committees related to forensic science and transportation safety.
Stern is an elected Fellow of the American Statistical Association (1998), the Institute of Mathematical Statistics (2011), the American Association for the Advancement of Science (2016), and the International Society for Bayesian Analysis (2020). He received the Founders Award from the American Statistical Association in 2022. He served as founding chair of the Department of Statistics at UC Irvine from 2002 to 2010 and as Dean of the Donald Bren School of Information and Computer Sciences from 2010 to 2016. Stern has also held leadership roles in professional organizations, including serving as Chair of Section U (Statistics) of the American Association for the Advancement of Science and as a founding member and later chair of the Advisory Committee on Forensic Statistics for the American Statistical Association.
Stern is co-author of Bayesian Data Analysis, a widely used textbook now in its third edition, which received the DeGroot Prize from the International Society for Bayesian Analysis in 2016. He has published extensively on statistical methodology and applications in areas ranging from sports analytics to neuroimaging studies. His public service has included participation on National Academy of Sciences panels examining motor carrier safety measurement, commercial vehicle driver fatigue, cybercrime measurement and the strengthening of forensic science at the National Institute of Justice. He served as co-principal investigator of the Center for Statistics and Applications in Forensic Evidence from 2015-2025, a multi-institutional research center funded by the National Institute of Standards and Technology.
Return to topEducation
- B.S. in Mathematics, Massachusetts Institute of Technology, 1981
- M.S. in Statistics, Stanford University, 1985
- Ph.D. in Statistics, Stanford University, 1987
Distinctions
- Distinguished Professor, UC Irvine, 2024
- Founders Award, American Statistical Association, 2022
- Fellow, American Association for the Advancement of Science, 2016
- Statistical Partnerships Among Academe, Industry and Government (SPAIG) Award, American Statistical Association, 2018
- National Associate of the National Research Council, 2011
- DeGroot Prize, International Society for Bayesian Analysis, 2016
- Fellow, International Society for Bayesian Analysis, 2020
- Fellow, Institute of Mathematical Statistics, 2011
- Fellow, American Statistical Association, 1998
- Chancellor's Professor, UC Irvine, 2018
- Laurence H. Baker Chair in Biological Statistics, Iowa State University, 2001-2002
Areas of Expertise
- Bayesian Statistical Methodology
- Hierarchical Modeling Techniques
- Forensic Statistics
- Sports Analytics
- Neuroimaging Data Analysis
- Early-Life Experience Quantification
Recent Publications
- Zou T., Stern H.S., “A Dirichlet process model for directional-linear data with application to bloodstain pattern analysis” (opens in new tab), Computational Statistics and Data Analysis, vol. 204, 2025.
- Arora H, Kaplan-Damary N, Stern HS, “Reliability of Ordinal Outcomes in Forensic Black-Box Studies” (opens in new tab), Forensic Science International, vol. 354, pp. 111909, 2024.
- Scurich N., Angel M., Stern H., Thompson W.C., “How signature complexity affects expert and lay ability to distinguish genuine, disguised and simulated signatures” (opens in new tab), Journal of Forensic Sciences, vol. 69, pp. 2159-2170, 2024.
- Arora H, Kaplan-Damary N, Stern HS, “Combining Reproducibility and Repeatability Studies with Applications in Forensic Science” (opens in new tab), Law, Probability and Risk, vol. 22, no. 1, 2023.
- Dai M, Stern HS, “A U-Statistic-Based Test of Treatment Effect Heterogeneity” (opens in new tab), Journal of Nonparametric Statistics, vol. 34, no. 1, pp. 141-163, 2022.
- Dai M, Shen W, Stern HS, “Sensitivity Analysis for the Adjusted Mann-Whitney Test with Observational Studies” (opens in new tab), Observational Studies, vol. 8, no. 1, pp. 1-29, 2022.
- Dai M, Shen W, Stern HS, “Nonparametric Tests for Treatment Effect Heterogeneity in Observational Studies” (opens in new tab), Canadian Journal of Statistics, vol. 51, no. 2, pp. 531-558, 2022.
- Friedman L, Stern H, Prokopenko V, Sjanian S, Griffith H, Komogortsev O, “Biometric Performance as a Function of Gallery Size” (opens in new tab), Applied Sciences Switzerland, vol. 12, pp. 11144, 2022.
- Zou T, Stern HS, “Towards a Likelihood Ratio Approach for Bloodstain Pattern Analysis” (opens in new tab), Forensic Science International, vol. 341, 2022.
- Longjohn R, Smyth P, Stern HS, “Likelihood Ratios for Categorical Count Data with Applications in Digital Forensics” (opens in new tab), Law, Probability and Risk, vol. 21, no. 2, pp. 91-122, 2022.
- Zou, T., Pan, T., Stern, H.S., “Recognition of Overlapping Elliptical Objects in a Binary Image” (opens in new tab), Pattern Analysis and Applications, vol. 24, pp. 1193-1206, 2021.
- HS Stern, DJ Richardson, M. Papaefthymiou, “Data Science and Computing: The View From a Sister Campus” (opens in new tab), Harvard Data Science Review, vol. 3, no. 2, 2021.
Most Cited Publications
- Gelman, A., Meng, X.-L., Stern, H. S., “Posterior Predictive Assessment of Model Fitness via Realized Discrepancies”, Statistica Sinica, vol. 6, pp. 733-807, 1996.
- Little, RJ, D'Agostino, R, Cohen, ML, Dickersin, K, Emerson, SS, Farrar, JT, Frangakis, C, Hogan, JW, Molenberghs, G, Murphy, SA, Neaton, JD, Rotnitzky, A, Scharfstein, D, Shih, WJ, Siegel, JP, Stern H, “The Prevention and Treatment of Missing Data in Clinical Trials” (opens in new tab), New England Journal of Medicine, vol. 367, no. 14, pp. 1355-1360, 2012.
- Gelman, A., Stern, H. S., “The Difference Between "Significant" and "Not Significant" is not Itself Statistically Significant” (opens in new tab), The American Statistician, vol. 60, no. 4, pp. 328-331, 2006.
- Sinharay, S., Stern H. S., Russell, D., “The Use of Multiple Imputation for the Analysis of Missing Data” (opens in new tab), Psychological Methods, vol. 6, pp. 317-329, 2001.
- Janzen, F. J., Stern, H. S., “Logistic Regression for Empirical Studies of Multivariate Selection” (opens in new tab), Evolution, vol. 52, pp. 1564-1571, 1998.
- Baram, T. Z., Davis, E. P., Obenaus, A., Sandman, C. A., Small, S. L., Solodkin, A., Stern, H., “Fragmentation and Unpredictability of Early-Life Experience in Mental Disorders” (opens in new tab), American Journal of Psychiatry, vol. 169, no. 9, pp. 907-915, 2012.
- Friedman, L., Stern, H., Brown, G. G., Mathalon, D., Turner, J., Glover, G. H., Gollub, R. L., Lauriello, J., Lim, K.O., Cannon, T., Greve, D. N., Bockholt, H. J., Belger, A., Mueller, B., Doty, M. H., He, J., Wells, W., Smyth, P., Pieper, S., Kim, S., et al., “Test-Retest and Between-Site Reliability in a Multicenter fMRI Study” (opens in new tab), Human Brain Mapping, vol. 29, no. 8, pp. 958-972, 2008.
- Sinharay, S., Johnson, M. S., Stern, H. S., “Posterior Predictive Assessment of Item Response Theory Models” (opens in new tab), Applied Psychological Measurement, vol. 30, no. 4, pp. 298-321, 2006.
- Molet, J., Heins, K., Zhuo, X., Mei, Y.T., Regev, L., Baram, T.Z., Stern, H., “Fragmentation and High Entropy of Neonatal Experience Predict Adolescent Emotional Outcome” (opens in new tab), Translational Psychiatry, vol. 6, 2016.
- Stern, H. S., “Neural Networks in Applied Statistics” (opens in new tab), Technometrics, vol. 38, pp. 205-220, 1996.
Contact Information
Website: https://www.ics.uci.edu/~sternh
Email: hal.stern@uci.edu
Phone: (949) 824-6296
Address: 510 Aldrich Hall, Irvine, CA 92697-1000
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Last updated on 2/25/2026.