About Me

About

Hi, my name is Bronson (Moonseong) Jeong and I’m a PhD candidate in Computer Science at UCLA, advised by Prof. Sriram Sankararaman. I work on methods at the interface of machine learning, statistics and biomedicine, with an emphasis on models that scale to biobank-size cohorts and remain interpretable & 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 worked on astronomical spectroscopy with Prof. Alice Shapley, which shaped how I think about inference under noise, confounding, and limited observability.

Research interests

• Biobank-scale genetic inference from summary statistics: fast, stable estimators for genetic parameters without individual-level data.
• High-dimensional phenotypes: “Train-free” foundation model to make 3D medical imaging and other complex phenotypes usable across tasks without heavy compute.
• EHR × genomics integration: interpretable models for risk prediction, phenotyping, and cohort discovery using longitudinal clinical records.
• 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.