Dr. Mehrotra is also an Adjunct Associate Professor of Biostatistics at the University of Pennsylvania and an elected Fellow of the American Statistical Association. He has served as a subject matter expert for the Bill and Melinda Gates Foundation, the US National Academy of Sciences and the International Council on Harmonization. His current primary focus is on statistical and machine learning approaches for enabling personalized medicine.

From 2011 to 2017, Dr. LaVange was director of the Office of Biostatistics in the United States Food and Drug Administration (FDA) Center for Drug Evaluation and Research (CDER). There, she oversaw more than 200 statisticians and other staff members involved in the development and application of statistical methodology for drug regulation. She was a leader in developing and assessing the effectiveness and appropriateness of innovative statistical methods intended to accelerate the process from drug discovery to clinical trials to FDA approval and patients’ benefit, with a particular focus on rare diseases. Prior to her government and academic experience, she spent 16 years in non-profit research and 10 years in the pharmaceutical industry. Dr. LaVange is an elected fellow of the American Statistical Association (ASA) and is the 2018 ASA President.

He is also a winner of the Shanti Swarup Bhatnagar Award in Mathematical Sciences, the National Award in Statistics and, the Young Researcher Award of IISA (USA). His current research interests are in Large dimensional random matrices, Free probability, High Dimensional Time series and Principal Agent Theory in economics. His earlier research areas include Resampling, Nonparametric Asymptotics, U-statistics, M_m estimates, Second order properties of sequential point and interval estimates and Statistical estimation in nonlinear parametric diffusion processes. With more than 50 Research collaborators, he has published over 120 articles in leading journals of Statistics, Probability and Economics. He has four books: Patterned Random Matrices; Large Covariance and Autocovariances Matrices (with Monika Bhattacharjee); Random Circulant Matrices (with Koushik Saha) and, U-Statistics, M_m-Estimates and Resampling (with Snigdhansu Chatterjee).

Her recent research has focused on Bayesian modelling and analysis of large data problems such as those arising in genomics. She is particularly interested in developing new analytical strategies for integrative and Translational Genomics, including clustering approaches, sparse (multiple) response models for genetic associations, risk prediction and hierarchical analysis of complex phenotypes. In 2009, Sylvia was awarded the Guy Medal in Silver from the Royal Statistical Society. She is a Fellow of the Institute of Mathematical Statistics, of the International Society for Bayesian Analysis and of the Academy of Medical Sciences in 2016. She has recently been nominated as President elect of the Royal Statistical Society.