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. The organizing question of my research is: how does the placenta’s isoform-resolved transcriptional landscape — shaped by both genetic variation and environmental exposures — mediate the programming of offspring health?

My work approaches this from three interconnected angles. First, I build the tissue-specific molecular resources needed to study the placenta at the right resolution, using long-read RNA sequencing to characterize transcript-isoform diversity that is invisible to standard gene-level approaches and missed by annotations derived from adult tissues. Second, I develop the causal inference tools needed to study developmental programming rigorously in observational birth cohorts, including novel frameworks that leverage multi-omic negative controls, genetically-predicted expression as instrumental variables, and generative adversarial networks to calibrate confounding bias in mediation analyses. Third, I functionally validate computationally prioritized candidates in experimental systems: isoform-specific knockdown in trophoblast cell lines, and patient-derived placental explant and organoid models in collaboration with faculty across institutions to test how candidate isoforms respond to glycemic and exposure conditions in physiologically relevant contexts.

I apply these tools to two primary exposures where the placenta is the obligate biological intermediary. In the context of gestational diabetes, I am building the largest multi-ancestry placental isoform-level dataset spanning 2,126 placentas across 8 cohorts and 5 ancestry groups to identify how maternal hyperglycemia alters placental isoform regulation through gene-by-environment interactions, and testing causal pathways linking these molecular responses to childhood metabolic risk. In the context of PFAS, I am investigating how prenatal exposure disrupts placental genomic imprinting and parent-of-origin isoform regulation, and how natural variation in transplacental transfer efficiency shapes transcriptional network architectures mediating effects on birth weight, gestational age, and offspring neurodevelopment. Ongoing work includes multi-cohort placental eQTL mapping, cross-ancestry fine-mapping, and colocalization studies linking isoform-level genetic regulation to birth and early-life outcomes.

In parallel, I maintain an independent bioinformatics consulting practice conducting pan-cancer genomic analyses to evaluate therapeutic targets using TCGA cohort data and DepMap CRISPR screens, identifying cancer-specific expression patterns, oncogenic pathway associations, and prognostic biomarker potential across multiple indications.

The long-term translational goal of this program is developing placental isoform signatures into early-pregnancy maternal blood-based screens that can identify at-risk pregnancies and inform targeted interventions during critical developmental windows, before complications manifest clinically.

I am currently seeking tenure-track Assistant Professor positions. See my CV for more details.