Fei Jiang

Fei Jiang, PhD, MS is an Associate Professor in the Department of Epidemiology & Biostatistics at the University of California, San Francisco (UCSF), School of Medicine. She previously served as an Assistant Professor in Statistics at the University of Hong Kong, where she contributed to the establishment of the Master of Data Science and Artificial Intelligence program. Her academic journey includes a Ph.D. in Statistics from Rice University, an M.S. in Biostatistics from The University of Texas at Houston, and a postdoctoral fellowship at Harvard University.

• Ph.D., Statistics, Rice University, Houston (2014)
• M.S., Biostatistics, The University of Texas at Houston (2010)
• Postdoctoral Fellow, Biostatistics, Harvard University, Boston (2016)

Dr. Jiang's research centers on machine learning, high-dimensional modeling, functional data analysis, and measurement error models, with applications in neuroimaging, genetics, stroke, cardiovascular disease, and digital health. Her work bridges statistical theory and practical medical challenges, particularly in clinical trial design and analysis of complex biomedical data. She has developed methods for adaptive randomization, change point detection, and functional quantile regression, applied to datasets such as BOSS (blood pressure and stroke outcomes).

Her recent publications reveal a strong trend in neuroimaging, oncology, and musculoskeletal health, with a focus on Alzheimer's disease, brain functional connectivity, osteoarthritis, and prostate cancer imaging. She frequently collaborates on interdisciplinary projects involving MEG/EEG, fMRI, and PET/MRI, leveraging advanced statistical frameworks to extract meaningful biological insights. Her work on digital twins for knee joints and brain metastasis atlases highlights her innovative approach to precision medicine.

Her scientific contributions have been recognized with awards including:

• Stroke and Vascular Neurology High Impact Paper Award (2018)
• ENAR Distinguished Student Paper Award (2013)
• Rice Graduate Student Fellowship (2012)

Dr. Jiang has secured significant research funding as Principal Investigator from the National Institutes of Health (NIH) and the Research Grants Council of Hong Kong. Her current projects include developing statistical tensor models for aneurysm growth prediction and machine learning frameworks for dementia. She has supervised and collaborated with numerous students and researchers, contributing to high-impact publications in journals like Nature Communications, NeuroImage, and Biometrics. She has also been involved in clinical trials related to acupuncture and pain management. Her lab, Jiang's Lab, focuses on creating data-driven tools for biomedical discovery.