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 program treats the placenta as both a clinically important tissue and a model system for questions at the intersection of evolutionary genomics, developmental biology, and epidemiological causal inference. Why does evolutionary conflict between parental genomes leave a specific imprint on regulatory architecture — and what happens when environmental exposures disrupt that equilibrium? How does the developing genome respond to environmental signals differently from adult tissues, encoding some of those responses at the isoform level in ways that persist through the life course? The placenta is uniquely positioned to address these questions: it is the primary somatic theater of maternal-fetal intragenomic conflict, its regulatory landscape has been substantially shaped by endogenous retrovirus co-option in ways that generate isoform complexity invisible to standard gene-level analyses, and it is the only major developmental organ accessible at population scale in humans — making it the rare tissue where fundamental questions in evolutionary genomics can be approached with the tools of population epidemiology.

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 — a particular problem in a tissue whose regulatory architecture is substantially derived from repetitive elements that short reads cannot resolve. 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. This work also bears on a broader question in developmental genomics: whether GxE regulatory architecture in a developmental tissue differs systematically — in effect size, variant class, and ancestry portability — from GxE effects mapped in stable adult tissues, which has implications for how we think about genetic risk across the life course. In the context of PFAS, I am investigating how prenatal exposure disrupts placental genomic imprinting and parent-of-origin isoform regulation — the molecular substrate of evolutionary conflict between maternal and paternal genomes — and how natural variation in transplacental transfer efficiency shapes the transcriptional network architectures mediating effects on birth weight, gestational age, and offspring neurodevelopment. Disruption of imprinting is interesting not only as a mechanism of developmental toxicity but as a probe of the conditions under which evolutionary equilibria between conflicting genomes break down. 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 goal of this program is twofold. Clinically, it aims to develop 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. Scientifically, it aims to use the placenta — a tissue at the confluence of intragenomic conflict, regulatory innovation, and developmental programming — to establish general principles about how genetic architecture operates during development, how evolutionary conflict is encoded in gene regulation, and how environmental exposures interact with the fetal genome to produce lasting phenotypic consequences.

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