Rajeshwari Sundaram, Ph.D.,M.S.
Biostatistics & Bioinformatics Branch
Dr Sundaram’s research is at the intersection of statistical methods and public health. Her interests include development of statistical methods for survival outcomes, especially multivariate survival outcomes and recurrent events, joint modeling of longitudinal data and survival data and hierarchical data with applications to reproductive outcomes, pediatrics and obstetrics. She is also interested in developing statistical methods for assessing the effects of chemical mixtures on health outcomes, especially pertaining to reproductive and child development, as well as methods for analyzing exposome type of data. Over past few years, she has worked to develop statistical methods aimed at building biologically meaningful models to better assess fecundity and fertility, with a focus on building individualized risk prediction for conception delay and infertility, issues of considerable interest due to the changing profile of couples attempting pregnancy for the first time. She is also currently interested in contributing to better guidelines for labor management in pregnant women by developing methods to address labor progression and by assessing labor arrests and other factors leading to medical intervention.Additionally, she is working on Machine Learning methods for analyzing data coming from continuous monitoring devices, like actigraphy. Additionally, she is working on machine learning methods for analyzing data coming from continuous monitoring devices, like actigraphy.
Rajeshwari Sundaram, M.Stat., Ph.D., is a senior investigator in the Biostatistics and Bioinformatics Branch since 2014. Dr Sundaram received her bachelor’s degree in Mathematics (Honors) from Calcutta University and a master’s degree in Applied Statistics and Data Analysis from Indian Statistical Institute, Calcutta, India. She received her Ph. D. in Statistics from Michigan State University. She join NICHD as a tenure track investigator in 2006, prior to which she was an assistant professor in University of North Carolina at Charlotte.
She is an elected fellow of American Statistical Association and International Statistical Institute. She is also recipient of Jeanne E. Griffith Mentoring Award from the Government Statistical Sections of the American Statistical Association. In addition, she has won the Outstanding Statistical Applications Award from American Statistical Association. She has also won multiple NIH Merit Awards as well as Travel award from American Women in Mathematics society. She is actively involved in various service to the Division, NICHD, NIH and statistical profession. In particular, she is the Chair of the Risk Analysis Section (2020). She serves as the chair of the professional development committee for her Division, NICHD representative on the Women Scientific Advisory Committee of NIH as well as the WSA liaison for Women in Biomedical Careers in NIH.
Sundaram R, Mumford SL, Buck Louis GM. Couples' body composition and time-to-pregnancy. Hum Reprod. 2017;32(3):662-668.
Lum KJ, Sundaram R, Buck Louis GM, Louis TA. A Bayesian joint model of menstrual cycle length and fecundity. Biometrics. 2016;72(1):193-203.
Lum KJ, Sundaram R, Louis TA. Accounting for length-bias and selection effects in estimating the distribution of menstrual cycle length. Biostatistics. 2015;16(1):113-28.
McLain AC, Sundaram R, Buck Louis GM. Joint analysis of longitudinal and survival data measured on nested timescales by using shared parameter models: an application to fecundity data. J R Stat Soc Ser C Appl Stat. 2015;64(2):339-357.
Sundaram R, McLain AC, Buck Louis GM. A survival analysis approach to modeling human fecundity. Biostatistics. 2012;13(1):4-17.
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Social and Behavioral Sciences
This page was last updated on June 11th, 2020