About me

I am a Postdoctoral Researcher at the Data Science Institute at Brown University, working with Sohini Ramachandran. Before that, I received my Ph.D. in Computational and Mathematical Engineering from Stanford University in 2023, where I was supervised by Noah Rosenberg.

My research focuses on method development in population genetics, computational biology, and data science. I use computational techniques such as machine learning, optimization, network analysis, and statistical inference to analyze complex genetic and genomic data.

Research overview

Methods

Population structure alignment

Tools and theory for aligning latent ancestries across repeated clustering runs and choices of K.

Statistical genetics

Multivariate association analysis

Machine-learning methods for effect-size shrinkage, gene-level aggregation, and pattern discovery.

Single-cell analysis

Alignment-aware clustering workflows

Model comparison and cluster interpretation for robust single-cell analysis pipelines.

Theory

Allele-sharing dissimilarities

Mathematical analysis of interpretable dissimilarity measures in population-genetic settings.

Selected work

2025 · Journal article · Theoretical Population Biology

Using mathematical constraints to explain narrow ranges for allele-sharing dissimilarities

2025 · Conference paper · RECOMB

ML-MAGES: A Machine Learning Framework for Multivariate Genetic Association Analyses

2024 · Journal article · Bioinformatics

Clumppling: cluster matching and permutation program with integer linear programming

News

Recent updates
  • On the academic job market and open to conversations about faculty and research opportunities.
  • Presenting ongoing work on clustering alignment for single-cell analysis at Genome Informatics 2025.
  • Attending Rising Stars in Data Science at Stanford University.