About me
I am an assistant professor of Environmental Health and Biostatistics in the Department of Environmental Medicine and Climate Science at Icahn School of Medicine, Mount Sinai. Along with Dr. Shoshannah Eggers, I serve as the co-director of the Microbial Exposomics Lab.
My research interest lies in developing and applying interpretable machine learning models for environmental health research. My primary research focuses on (1) understanding how prenatal exposure to environmental chemicals, particularly metals, and dysregulation in their homeostasis affect childhood or adolescent health and (2) how the gut microbiome modifies these effects. Similar to the concept of gene signature, I introduced the idea of exposure clique models in environmental health to identify subgroups of the population with certain patterns of chemical exposures.
Previously I did a Post Doctoral Fellowship with Damaskini Valvi at the Icahn School of Medicine, Mount Sinai, where I developed integrated statistical models to study how early life and life-course exposure to environmental chemicals impact cardio-metabolic health outcomes, with a particular focus on the mixture-effects and interactions of endocrine disrupting chemicals. I received PhD from Division of Biostatistics and Bioinformatics at the Pennsylvania State University under Jason Liao and Arthur Berg. I wrote my thesis on Frequentist and Bayesian hypothesis testing with a focus on meaningful effect sizes to enhance reproducibility in scientific studies. Before joining Penn State, I completed B.Sc. (Bachelor of Science) in Statistics from St. Xavier’s College, Kolkata, India and M.Stat (Masters of Statistics) from Indian Statistical Institute. I am a serious Matcha green tea aficionado. Outside of studies, I enjoy the outdoors, long-distance running, rowing, and volleyball.
My current research can be broadly divided into three categories:
Machine-learning in environmental health
Exposomics, microbiome and human health
Environmental epidemiology