Brian Williamson, PhD


“Everyone deserves accessible, affordable, and high-quality health care. Rigorous statistical methods and a focus on justice can help achieve this goal.”

Brian Williamson, PhD

Assistant Biostatistics Investigator, Kaiser Permanente Washington Health Research Institute
Affiliate Investigator, Biostatistics, Bioinformatics, and Epidemiology Program, Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Center


Brian Williamson, PhD, is a biostatistician with expertise in statistical epidemiology, semiparametric and nonparametric estimation theory, and high-dimensional estimation and prediction. He is interested in developing robust procedures for statistical inference when machine learning is used to address problems in public health, and in working toward equity, diversity, and inclusion in biomedical research and practice. A central theme of his research is on identifying clinically useful biomarkers and assessing their performance.

Before joining Kaiser Permanente Washington Health Research Institute, Dr. Williamson completed his postdoctoral research training at the Fred Hutchinson Cancer Research Center. During his time at Fred Hutch, Dr. Williamson developed statistical methods to address issues arising in the development of biomarker panels for use in risk prediction, screening, and diagnosis. Dr. Williamson also collaborated with researchers from the Women’s Health Initiative to assess the utility of metabolomic biomarkers for predicting breast and colorectal cancer; with researchers from the HIV Vaccine Trials Network (HVTN) to aid in selecting candidate broadly neutralizing antibody regimens to advance to HIV prevention clinical trials; and was a part of the Coronavirus Prevention Network Biostatistics Team.

Dr. Williamson received his PhD in biostatistics from the University of Washington. His dissertation focused on a general framework for performing inference on model-free variable importance measures. With colleagues from the HVTN, he used this framework to identify features of the HIV viral genome that may be important in predicting viral susceptibility to the broadly neutralizing antibody VRC01.

At KPWHRI, Dr. Williamson collaborates on projects across a range of research areas including mental health, pragmatic clinical trials, and drug and vaccine safety and effectiveness.

Recent Publications

Carrell DS, Floyd JS, Gruber S, Hazlehurst BL, Heagerty PJ, Nelson JL, Williamson BD, Ball R. A general framework for developing computable clinical phenotype algorithms. J Am Med Inform Assoc. 2024 May 15:ocae121. doi: 10.1093/jamia/ocae121. Online ahead of print. PubMed

Magaret C, Li L, deCamp A, Rolland M, Juraska M, Williamson B, Ludwig J, Molitor C, Benkeser D, Luedtke A, Simpkins B, Carpp L, Bai H, Deariove B, Greninger A, Roychoudhury P, Sadoff J, Gray G, Roels S, Vandebosch A, Stieh D, Le Gars M, Vingerhoets J, Grinsztejn B, Goepfert P, Truyers C, Van Dromme I, Swann E, Marovich M, Follmann D, Neuzil K, Corey L, Hyrien O, Paiva de Sousa L, Casapia M, Losso M, Little S, Gaur A, Bekker LG, Garrett N, Heng F, Sun Y, Gilbert P. Quantifying how single dose Ad26.COV2.S vaccine efficacy depends on Spike sequence features.  Nat Commun. 2024;15(1):2175. doi: 10.1038/s41467-024-46536-w.  PubMed

Williamson BD, Huang Y. Flexible variable selection in the presence of missing data. Int J Biostat. 2024 Feb 13. doi: 10.1515/ijb-2023-0059. [Epub ahead of print]. PubMed

Juraska M, Bai H, deCamp AC, Magaret CA, Li L, Gillespie K, Carpp LN, Giorgi EE, Ludwig J, Molitor C, Hudson A, Williamson BD, Espy N, Simpkins B, Rudnicki E, Shao D, Rossenkhan R, Edlefsen PT, Westfall DH, Deng W, Chen L, Zhao H, Bhattacharya T, Pankow A, Murrell B, Yssel A, Matten D, York T, Beaume N, Gwashu-Nyangiwe A, Ndabambi N, Thebus R, Karuna ST, Morris L, Montefiori DC, Hural JA, Cohen MS, Corey L, Rolland M, Gilbert PB, Williamson C, Mullins JI. Prevention efficacy of the broadly neutralizing antibody VRC01 depends on HIV-1 envelope sequence features. Proc Natl Acad Sci U S A. 2024;121(4):e2308942121. doi: 10.1073/pnas.2308942121. Epub 2024 Jan 19.  PubMed

Smith JC, Williamson BD, Cronkite DJ, Park D, Whitaker JM, McLemore MF, Osmanski JT, Winter R, Ramaprasan A, Kelley A, Shea M, Wittayanukorn S, Stojanovic D, Zhao Y, Toh S, Johnson KB, Aronoff DM, Carrell DS. Data-driven automated classification algorithms for acute health conditions: Applying PheNorm to COVID-19 disease. J Am Med Inform Assoc. 2023 Dec 18:ocad241. doi: 10.1093/jamia/ocad241. [Epub ahead of print]. PubMed




KPWHRI begins new phase of flu surveillance

KPWHRI receives $10 million to continue vaccine effectiveness research for flu, COVID-19, and other respiratory diseases.

Vaccine Safety


Biostatisticians track COVID-19 vaccine safety

Dr. Jennifer Nelson explains how KP scientists are helping the CDC and FDA keep an eye out for rare adverse events.

mental health


$10 million to expand Mental Health Research Network

NIMH funding will enable the MHRN to conduct larger studies in integrated health systems on topics that matter most.