At NYU Langone Medical Center, I ran end-to-end analyses across single-cell, bulk, chromatin, and whole-genome sequencing data. I also built computational approaches for gene-regulatory networks and 3D chromatin, including an in-silico screen of more than 100,000 perturbations across 150+ patient datasets.
My recent work evaluates AI output in genomics. I designed a pre-registered study of AI agents with deterministic Python graders, and a reproduction campaign on public GEO data surfaced a failed immunoprecipitation that the paper’s depth-only QC had missed.
I’ve maintained open-source Hi-C and HiChIP pipelines, supervised PhD students on 3D chromatin projects, and contributed research published in Molecular Cell and Nature Biotechnology. I’m especially interested in making computational genomics results reproducible and checking them against independent evidence.
