About Me

About

Hi, my name is Bronson (Moonseong) Jeong and I’m a PhD student in Computer Science at UCLA, advised by Professor Sriram Sankararaman. I work on methods at the interface of statistical genetics, machine learning, and clinical informatics, with an emphasis on models that scale to biobank-size cohorts and remain interpretable and reproducible. Specifically, my research is focused on understanding the genetic basis of complex traits (such as height or diseases). As an undergrad, I studied Mathematics of Computation and Physics also at UCLA, and led data analysis in an astronomical spectroscopy project with Professor Alice Shapley. This was an experience that shaped my approach to signal detection and uncertainty quantification in large, noisy datasets.

Research interests

• Population-scale genetic inference: Efficient estimators using summary statistics to recover architecture and population parameters when raw data are constrained.
• High-dimensional phenotypes: “Train-free” representations (RAPTOR) to make medical imaging and other complex phenotypes usable across tasks without heavy compute.
• EHR × genomics integration: Methods that combine clinical records with genomic features for interpretable risk prediction and cohort discovery.
• Opioid prescription data: Preventing opioid addiction by disentangling the California CURES database for controlled substances.
• Theory for ancestry-aware models: Coalescent-theoretic limits and robustness for reference-based local ancestry inference.