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SUNY Downstate Health Sciences University

School of Public Health

Profile

Photo of Usha Govindarajulu

Usha Govindarajulu, PhD, MS

Assistant Professor

Department of Epidemiology and Biostatistics

Tel: (718) 221-6599 • Fax: (718) 221-5157

e-mail: Usha.Govindarajulu@downstate.edu

Academic Qualifications:
  • 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.

Interviews:

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.

 

Selected Presentations:

 

  • "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