I build computational solutions for biohealth problems, including cancer detection and fundamental genomics research. I currently work at Exai Bio to build our computational platform. Our team develops scalable, robust and accurate approaches for early-cancer detection using cell-free RNAs and generative AI.

2024 — NowExai BioStaff Software Engineer, Computational Genomics

2024 — Now

California, United States

Develop computational methods to process cell-free RNA (cfRNA) data for Exai Bio's liquid biopsy platform.

The methods include sequence alignment, trimming, deduplication, sequence quantification and variant calling.

Evaluate machine learning model performance to support model development and decision making.

2023 — 2024Exai BioSenior Software Engineer, Computational Genomics

2023 — 2024

California, United States

Co-led the software development life cycle management of the bioinformatics engineering platform.

Aggregated, cleaned and managed datasets to facilitate machine learning model development.

2022 — 2023Exai BioSoftware Engineer, Computational Genomics

2022 — 2023

California, United States

Developed and optimized the core R&D bioinformatics pipeline to process 100+k samples.

2018 — 2022The Johns Hopkins UniversityDoctoral Student

2018 — 2022

Baltimore, Maryland, United States

* Advised by Dr. Ben Langmead

* Developed the "levioSAM2" software to improve alignment using a complete reference genome and lift-over (Nature Methods 2023)

* Developed computational methods to improve alignment using population genomic information ("reference flow", Genome Biology 2021; "levioSAM", Bioinformatics 2021)

* Analyzed the HLA allele typing performance of a graph-based sequence alignment method ("FORGe", Genome Biology 2018)

2021 — 2021The Johns Hopkins UniversityTeaching Assistant

2021 — 2021

Baltimore, Maryland, United States

Sketching and Indexing (Dr. Ben Langmead), Department of Computer Science