I am an Associate Data Scientist in the Department of Epidemiology at the University of Texas MD Anderson Cancer Center with Dr. Arjun Bhattacharya and Dr. Paul Scheet. My research investigates how gene regulatory mechanisms influence human development and health across the life course. I integrate multi-omic approaches with statistical genetics, causal inference methods, and machine learning to uncover how genomic and environmental factors shape developmental trajectories and disease risk.

I develop mechanistic, isoform-resolved models of gene regulation that extend beyond traditional gene-level associations to capture the molecular complexity underlying human development and disease. Using long-read RNA sequencing and computational genomics, I characterize transcript-isoform diversity in the human placenta and apply fine-mapping approaches to identify genetic variants that regulate parent-of-origin-specific expression. This work reveals how alternative splicing and genomic imprinting create functionally distinct transcripts that respond differentially to environmental exposures—providing molecular specificity that traditional approaches miss. I investigate how prenatal PFAS exposure disrupts placental genomic imprinting and transcript-isoform regulation, with downstream effects on social responsiveness and neurodevelopment, and examine how gestational diabetes alters placental isoform landscapes across diverse populations, testing causal pathways linking maternal metabolic dysfunction to fetal growth and childhood metabolic risk.

To address unmeasured confounding in observational birth cohort studies, I develop novel causal inference frameworks that leverage multi-omic negative controls and genetically-predicted expression to strengthen causal claims about developmental programming mechanisms. A long-term goal is translating placental transcriptomic signatures into maternal blood-based screens that can identify pregnancy complications and offspring risk for metabolic and neurodevelopmental disorders early in gestation. By combining isoform-resolved placental biomarkers with Bayesian prediction models and cross-population validation, my work aims to develop clinically deployable assays that enable precision prenatal care and targeted interventions during critical developmental windows.

I am currently seeking tenure-track Assistant Professor positions to investigate: What epigenomic changes during pregnancy contribute to the increased breast cancer risk and decreased survivorship associated with increased parity? How do environmental contaminants unique to rural areas (agricultural chemicals, oil/gas extraction byproducts) influence cancer prognosis and placental function? Do placental biomarkers from pregnancies affected by maternal dietary patterns or use of alcohol, tobacco, or cannabis predict childhood metabolic and neurodevelopmental outcomes, and can we leverage these for development of targeted assays for detection and prevention in vulnerable populations?

See my CV for more details.