Dr. Bright is the first Black woman to earn a doctorate in biomedical informatics within the United States and the first Black student to earn a doctorate in this field from Columbia University. As such, she uses her platform and work to advance diversity, equity, and inclusion in informatics and the data science profession through local and national initiatives. In addition to speaking with students about the importance of diversity in science, Dr. Bright also works with organizations to create diverse and inclusive environments.


Ph.D., Biomedical Informatics, Columbia University
B.S., Information Systems, University of Maryland, Baltimore County

B.A., Sociology, The College of William and Mary



Postdoctoral Fellowship, Duke University
Medical Informatics Trainees Summer Rotation, National Library of Medicine

Summer Research Internship, University of California, San Francisco
Intramural Research Summer Internship, National Institutes of Medicine


American Medical Informatics Association (AMIA) Leadership Award

American College of Medical Informatics (ACMI) Elected Fellow

blackcomputeHER Fellow

Center for Interdisciplinary Research to Reduce Antimicrobial Resistance Predoctoral Fellow, Columbia University

Biomedical Informatics Predoctoral Fellow, National Library of Medicine

Meyerhoff Scholar, University of Maryland, Baltimore County

Professional Memberships

American Medical Informatics Association (AMIA)

Association for Computing Machinery (ACM) and ACM SIGBio

Association for Women in Science (AWIS)

Healthcare Information and Management Systems Society

National Society of Black Engineers (NSBE)

Society for Advancement of Chicanos/Hispanics and Native Americans in Science (SACNAS)

Select Leadership Activities


Dr. Tiffani J Bright is a nationally-recognized applied clinical informatics leader, with expertise in design, implementation, and evaluation of clinical decision support (CDS) systems, electronic guideline-delivery platforms, and optimization of electronic health records (EHRs). She combines her data science expertise with her diversity, equity, and inclusion (DEI) skillset to bring an equity-centered framework to the research projects she is leading and collaborating, particularly around workforce diversity, data diversity, and algorithmic fairness.