SUNY Downstate Health Sciences University
School of Public Health
Usha Govindarajulu, PhD, MS
Department of Epidemiology and Biostatistics
Tel: (718) 221-6599 • Fax: (718) 221-5157
- Post-Doctoral: Harvard University, School of Public Health
- PhD: Boston University
- MS: George Washington University
Background and Expertise:
Dr. Usha Govindarajulu is an Assistant Professor of Biostatistics. She received her PhD in Biostatistics from Boston University, her MS in Biostatistics from George Washington University, and her AB from Cornell University. She also did her post-doctoral work in Biostatistics at Harvard School of Public Health.
Dr. Govindarajulu's major statistical research interests are in survival analysis, frailty models, causal inference, genetic epidemiology, smoothing, and non-parametrics. Her area of medical expertise is in cardiology, allergy and immunology, infectious disease (HIV) , radiology, and translational research. In public health, she is involved with health disparities and community health research.
She is a Co-Editor of Computational Statistics. She is also a member of the American Statistical Association since 1998 and is currently Program Chair-Elect for the Section of Statistical Computing.
- Public health minute: https://soundcloud.com/publichealthminute/phm-learning-curves-govindarajulu
- BBC interview: https://vimeo.com/151702021
- Marquis Who’s Who 2018: https://www.24-7pressrelease.com/press-release/452093/Marquis-Whos-Who-Recognizes-Usha-Govindarajulu-PhD-MS-for-Contributions-to-Biomedical-Science
- Marquis Top Educator 2018: https://marquistopeducators.com/2018/05/01/usha-govindarajulu/
My main contribution to science is in the area of survival analysis and frailty models. This has been my main area of investigation from my doctoral work. My selected publications highlight this area of research.
My other contribution in terms of applied work is in applications to cardiology and allergy/immunology. I have a background of research in immunology since high school so have a good biological understanding of the processes and also I first started my niche in cardiology through the Framingham Heart Study when I was doing my doctoral work. The publications below show my ongoing interests.
- Govindarajulu US and Malloy EJ. (2015). "Evaluating treatment effect in multicenter trials with small centers using survival modeling." International Journal of Statistics in Medical Research 4: 8-25.
- Sloane D, Govindarajulu U, Harrow-Mortelliti J, Barry W, Hsu FI, Hong D, Laidlaw T, Palis R, Legere H, Bunyavanich S, Breslow R, Wesemann D, Barrett N, Brennan P, Chong HJ, Liu A, Fernandez J, Fanning L, Kyin T, Cahill K, Bankova L, Lynch A, Berlin S, Campos S, Fuchs C, Mayer R, Matulonis U, and Castells M. (2016) "Safety, Costs, and Efficacy of Rapid Drug Desensitizations to Chemotherapy and Monoclonal Antibodies" JACI: In Practice (in press)
- Govindarajulu US, Matheny M, Goldfarb D, Stillo M, and Resnic F (2017) "Learning curve estimation in medical devices and procedures: hierarchical modeling" Statistics in Medicine 36: 2764-2785.
- Govindarajulu US, Goldfarb D, and Resnic R (2018).“Real data applications of learning curves in cardiac devices and procedures” Journal of Medical Statistics and Informatics. 6(2): : http://dx.doi.org/10.7243/2053-7662-6-2
- Govindarajulu US, Bedi S, Kluger A, and Resnic R (2018). “Survival analysis of hierarchical learning curves in assessment of cardiac device and procedural safety” Statistics in Medicine. 37(28): 4185-4199.
- "Misclassification Probabilities of n-fold Random Samples". Joint Statistical Meetings. Miami, Florida, August 2011.
- "Frailty models: Applications to biomedical and genetic studies". University of Nevada, Las Vegas, Statistics Dept, November 2014
- Evaluating Treatment Effect in Multicenter Trials with Small Centers Using Survival Modeling"Joint Statistical Meetings. Seattle, WA, August 2015; Symposium on Statistical and Computational Methods for Pharmacogenetic Epidemiology of Cancer. Memorial Sloan-Kettering, New York, NY August 2016.
- "Statistical methods for dose-response estimation and implications for public health" SUNY Downstate Brooklyn Health Disparities Seminar. October 2016.
- "Learning curve estimation in medical devices and procedures: hierarchical modeling" Joint Statistical Meetings, Baltimore, Maryland, August 2017
- “Real Data Applications of Learning Curves in Cardiac Devices and Procedures” Joint Statistical Meetings, Vancouver, Canada July 2018.
- “Introduction to Research Study Design.” Internal Medicine residents. SUNY Downstate Medical Center. Brooklyn, NY. October 2018.