Biography

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.