Research

  • Pathway-Independent Genetic Signals in Type 2 Diabetes Clusters

    Student Researcher, Massachusetts General Hospital

    • Investigating whether data-driven genetic clusters in type 2 diabetes capture biological information beyond curated pathway-based polygenic scores.
    • Constructing individual-level cluster-specific scores from variant-level disease clusters and comparing them with pathway-based pPGS derived from Reactome and KEGG.
    • Studying whether residual cluster signals can reveal novel or cross-pathway disease mechanisms.
    • Type 2 diabetes
    • Polygenic scores
    • Genetic clustering

  • Scaling Laws in Single-Cell Representation Learning

    Student Researcher, Harvard T.H. Chan School of Public Health

    • Applying Random Matrix Theory to derive mutual-information-based measures for biological signal recovery in single-cell multi-omics data.
    • Developing theoretical scaling laws for cell number, sequencing depth, and batch effects in single-cell data.
    • Conducting real-data analyses to evaluate how representation learning embeddings recover biological information.
    • Single-cell multi-omics
    • Random Matrix Theory
    • Representation learning

  • Survival Analysis in Oncology Clinical Trials

    Student Researcher, Johns Hopkins University

    • Performed survival analysis on multi-arm oncology clinical trial data.
    • Constructed time-to-event endpoints for staggered therapy initiation, treatment discontinuation, and right-censoring.
    • Conducted Kaplan-Meier analysis, median survival estimation, and Cox proportional hazards modeling with clinical covariates.
    • Survival analysis
    • Cox modeling
    • Clinical trials

  • Single-Cell Sequencing Analysis of Blood Tissue Samples

    Student Researcher, The Chinese University of Hong Kong

    • Analyzed single-cell sequencing data from blood tissue samples to study cellular-level molecular profiles.
    • Used PCA and Leiden clustering to identify heterogeneous cell populations and annotate cells with marker genes.
    • Applied cellular enrichment analysis to connect marker genes with disease-related biological signals.
    • Single-cell analysis
    • Leiden clustering
    • Cell annotation

Academic

  • Johns Hopkins University

    Teaching Assistant

    • Bayesian Statistics

  • Academic Service

    Peer Reviewer

    • Current Medical Imaging
    • CMC-Computers, Materials & Continua
    • Journal of Intelligent & Fuzzy Systems
    • Journal of Computer Science
    • Journal of Fuzzy Logic and Modeling in Engineering