Jing Zhou, PhD


“I am passionate about using big data and cutting-edge statistical methods to address health-related problems to help people live a healthier life through better health care.”

Jing Zhou, PhD

Senior Collaborative Biostatistician, Kaiser Permanente Washington Health Research Institute



Jing Zhou, PhD, is a biostatistician with expertise in Bayesian modeling, machine learning methods, dimension reduction and variable selection methods, joint models, group sequential design in clinical trials, and more. She is particularly interested in leveraging big data, applying appropriate methods, and developing novel approaches to address challenging health-related research problems to help patients receive better health care. At Kaiser Permanente Washington Health Research Institute (KPWHRI), Dr. Zhou collaborates on projects across a range of research areas including aging and cognitive function, behavioral health, and mental health.

Before joining KPWHRI, Dr. Zhou was a statistician at Genentech, a world-leading biotechnology company. At Genentech, she collaborated with scientific partners and project teams on multiple clinical trials. As the lead statistician, she designed and monitored clinical trials and analyzed results for concise interpretations and conclusions that ultimately resulted in scientific publications and drug approvals. During her second year at Genentech, Dr. Zhou mentored an intern in developing a new Bayes method to effectively borrow information among sub-cohorts in an early-phase umbrella trial.

Dr. Zhou completed her PhD in biostatistics at the University of North Carolina at Chapel Hill. Her dissertation research proposed methods to identify associations between birth defects and parental and environmental factors in the National Birth Defects Prevention Study, which drew from a large national database. In this research, she developed innovative non-parametric Bayes methods to overcome the curse of dimensionality and detect significant risk factors for multiple birth defects.

Research interests and experience

  • Biostatistics

    Bayesian modeling, dimension reduction, variable selection, longitudinal analysis, machine learning methods

  • Aging & Geriatrics

    Biostatistics, dementia, observational studies, risk prediction, joint modeling, measurement error, causal inference

  • Behavior Change

    Biostatistics, clinical trials, sedentary behavior, fitness device data

Recent publications

Vuylsteke P, Huizing M, Petrakova K, Roylance R, Laing R, Chan S, Abell F, Gendreau S, Rooney I, Apt D, Zhou J, Singel S, Fehrenbacher L. Pictilisib plus paclitaxel for the treatment of hormone receptor-positive, HER2-negative, locally recurrent, or metastatic breast cancer: interim analysis of the multicentre, placebo-controlled, phase II randomised PEGGY studypeggy study Ann Oncol. 2016 Nov;27(11):2059-2066. Epub 2016 Aug 29. PubMed

Zhou J, Bhattacharya A, Herring AH, Dunson DB. Bayesian factorizations of big sparse tensors. J Am Stat Assoc. 2015;110(512):1562-1576. doi: 10.1080/01621459.2014.983233. Epub 2016 Jan 15. PubMed

Zhou J, Herring AH, Bhattacharya A, Olshan AF, Dunson DB, National Birth Defects Prevention Study. Nonparametric Bayes modeling for case control studies with many predictors. Biometrics. 2016 Mar;72(1):184-92. doi: 10.1111/biom.12411. Epub 2015 Sep 22. PubMed

Zhou J, Adewale A, Shentu Y, Liu J, Anderson K. Information-based sample size re-estimation in group sequential design for longitudinal trials. Stat Med. 2014 Sep 28;33(22):3801-14. doi: 10.1002/sim.6192. Epub 2014 May 4. PubMed

Zhang S, Barros SP, Moretti AJ, Yu N, Zhou J, Preisser JS, Niculescu MD, Offenbacher S. Epigenetic regulation of TNFA xpression in periodontal disease. J Periodontol. 2013 Nov;84(11):1606-16. doi: 10.1902/jop.2013.120294. Epub 2013 Jan 31. PubMed


aging & geriatrics


Do drugs cause falls for adults with dementia?

Researchers find a relationship between prescribed central nervous system-active medications and increased risk of falling among older people with dementia.

alzheimer's research


Eye conditions may help screen for Alzheimer’s disease

Age-related macular degeneration, diabetic retinopathy, glaucoma could be new lens on dementia risk.