F. DuBois Bowman

F. DuBois Bowman

F. DuBois Bowman

Chair and Cynthia and Robert Citrone-Roslyn and Leslie Goldstein Professor
Biostatistics

Office/Address:

722 West 168th Street, Mail Code: 6th Floor
New York NY United States 10032
Phone:
212 342 4254

Biography

Dr. Bowman is a renowned expert in the statistical analysis of brain imaging data and other complex data. His work mines massive data sets and has important implications for mental and neurological disorders such as Parkinson's disease, Alzheimer's disease, and depression. His research has helped to reveal brain patterns that reflect disruption from psychiatric diseases, detect biomarkers for neurological diseases, and determine more individualized therapeutic treatments. Additionally, his research seeks to determine threats to brain health from environmental exposures and to optimize brain health in aging populations. Dr. Bowman leads a department at Columbia with exciting research strengths in analytic capabilities for big data, for instance, derived from smart phones, wearable devices, hospital records, genomics, and brain imaging scanners. Dr. Bowman has an exciting vision to leverage these strengths to make Columbia a national hub for the mining, analysis, and development of novel methods for massive data sets to tackle major public health and medical problems. Dr. Bowman is a Fellow of the American Statistical Association and previously served as President of the Eastern North American Region (ENAR) of the International Biometric Society. Dr. Bowman was formerly a tenured professor in the Department of Biostatistics and Bioinformatics at Emory University.

Topics

Education

PhD, 2000, University of North Carolina
MS, 1995, University of Michigan
BS, 1992, Morehouse College

Columbia Affiliations

Health Analytics, Committee, Data Science Institute

Academic Appointments

Chair, Biostatistics

Other Affiliations

Fellow of the American Statistical Association
Past President, ENAR, International Biometric Society

Areas of Expertise

Alzheimer's Disease, Big Data, Imaging Data, Longitudinal Studies, Spatial Analysis, Depression, Mental Health, Schizophrenia
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