Nice to meet you!
I'm currently wrapping up a PhD in computational genetics.
I have a broad interest in building software of tomorrow for all kinds of research applications —
alternative asset markets, DNA biobanks, and more.
I'm excited and highly motivated to take on new challenges at new scale.
This website is actively under construction. Check back later for more.
Want to get in touch? Connect with me on LinkedIn or send me an email!
My doctoral work in the
Below Lab involves innovation in genetic relatedness analysis.
I have developed and contributed as a first author to publications on software
that leverages biobank scale identity-by-descent (IBD) data to characterize
novel disease-gene associations, build family pedigrees in sparse datasets, and more.
Built with: Python, Perl, PLINK, Docker
Overview: Pedigree generation software that maximizes the utility of two different kinds of genomic segment metadata: global sharing proportions from PRIMUS and segment length & distribution from ERSA.
Built with: C++, Python, SQLite
Overview: Scalable map-reduce approach to identifying IBD segment-based enrichment of binary trait disease case status in large datasets. We enable phenome-wide analysis that outperforms traditional association-based methods like GWAS.
Vanderbilt University School of Medicine | Doctoral Candidate, Human Genetics
↳ Teaching Assistant, Python (2021-2022)
↳ Award Recipient, Big Biomedical Data Science Training Program (2020-2021)
↳ Award Recipient, Dean's Award (2019-2020)
Duke University | B.S., Biology with Distinction | Class of 2019
I have published two research manuscripts as a first author, two as a supporting author, and contributed to dozens of conference abstracts and presentations. I additionally have two first author manuscripts in preparation that cover the extent of my thesis aims. More information is available on my Google Scholar profile.