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.
Bayesian modeling, dimension reduction, variable selection, longitudinal analysis, machine learning methods
Biostatistics, dementia, observational studies, risk prediction, joint modeling, measurement error, causal inference
Biostatistics, clinical trials, sedentary behavior, fitness device data
Barnes DE, Zhou J, Walker RL, Larson EB, Lee SJ, Boscardin WJ, Marcum ZA, Dublin S. Development and validation of eRADAR: a tool using EHR data to detect unrecognized dementia. J Am Geriatr Soc. 2020 Jan;68(1):103-111. doi: 10.1111/jgs.16182. Epub 2019 Oct 14. PubMed
Soria JC, Adjei AA, Bahleda R, Besse B, Ferte C, Planchard D, Zhou J, Ware J, Morrissey K, Shankar G, Lin W, Schutzman JL, Dy GK, Groen HJM. A phase IB dose-escalation study of the safety and pharmacokinetics of pictilisib in combination with either paclitaxel and carboplatin or pemetrexed and cisplatin in patients with advanced non-small cell lung cancer. Eur J Cancer. 2017 Nov;86:186-196. doi: 10.1016/j.ejca.2017.08.027. Epub 2017 Oct 6. PubMed
Leong S, Moss RA, Bowles DW, Ware JA, Zhou J, Spoerke JM, Lackner MR, Shankar G, Schutzman JL, van der Noll R, Voest EE, Schellens JHM. A phase I dose-escalation study of the safety and pharmacokinetics of pictilisib in combination with erlotinib in patients with advanced solid tumors. Oncologist. 2017 Aug 10. pii: theoncologist.2017-0090. doi: 10.1634/theoncologist.2017-0090. [Epub ahead of print]. PubMed
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
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