Stephen J. Gange, PhD
Senior Associate Dean for Academic Affairs
Center & Institute Affiliation(s):
615 N. Wolfe Street, W1513
Baltimore , Maryland 21205
PhD , University of Wisconsin , 1994
Research interests include epidemiologic and statistical methods for cohort studies, data science, evaluation of therapies and biomarkers in observational studies, epidemiology and pathogenesis of HIV/AIDS and data management and statistical coordinating centers.
For nearly 20 years, I have worked primarily in HIV/AIDS with experience and scientific leadership that spans basic, clinical, epidemiological, and policy-level research including the Women's Interagency HIV Study (WIHS), the largest nationwide cohort study devoted to the study of HIV-infected women and the Epidemiology/Biostatistics Core Director for the North American AIDS Cohort Collaboration of Research and Design (NA-ACCORD), an International Epidemiologic Databases to Evaluate AIDS (IeDEA) initiative.
In addition to methodological and HIV/AIDS research, I have worked on studies of HPV, substance abuse, and molecular biomarkers for liver cancer with investigators across the University.
Honors and Awards
- Adjunct Professor, Indian Institute of Health Management Research (IIHMR), Jaipur, India (2013-present)
- JHU Leadership Development Program, School of Medicine Master Mentor Program, and Provost’s Academic Leadership Program (2012-13)
- Invited Member, American Epidemiological Society, 2012
- Fellow, American College of Epidemiology, 2010
- Faculty Senate, President, 2008-9.
- Advising, Mentoring, and Teaching Recognition Award (AMTRA) from Student Assembly, Johns Hopkins School of Public Health, 2005.
- Elected Member, Delta Omega Honorary Public Health Society,Alpha Chapter, Johns Hopkins School of Public Health, 2002.
- AIDS Clinical Studies and Epidemiology Study Section, 2001-6.
- Biometrics Society (ENAR) Student Travel Award, 1994. Paper also selected as one of top submissions.
- Society of Clinical Trials Student Scholarship Travel Award, 1994.
- Epidemiologic Methods
- Data science
- Observational Studies
- Cohort Studies
- Quantitative Methodology
- Data Management