Justin Hong
Algorithm Development Intern at Hudson River Trading
New York, New York, United States
Summary
🤩
Rockstar🎓
Top SchoolJustin Hong is a Ph.D. candidate in computer science at Columbia University and an algorithm development intern at Hudson River Trading, bringing a decade of experience at the intersection of software engineering and computational biology. He has built production-grade probabilistic modeling software—contributing code and documentation to the widely used scvi-tools project—while also implementing new models like LDA within its Pyro-based framework. His background spans industry roles at Nuro and Palantir and research engineering at UC Berkeley, where he added JAX support to deep-learning codebases. Justin combines rigorous theory (MS/BS from UC Berkeley) with practical systems work, routinely moving research methods into usable software for single-cell and spatial omics. He’s equally comfortable optimizing back-end pipelines and polishing documentation, a balance that helps translate complex biology into reproducible analyses.
10 years of coding experience
4 years of employment as a software developer
Bachelor’s Degree Computer Science and Molecular and Cell Biology, Bachelor’s Degree Computer Science and Molecular and Cell Biology at University of California, BerkeleyMaster of Science - MS EECS, Master of Science - MS EECS at UC Berkeley College of EngineeringHigh School, High School at Acton-Boxborough Regional High SchoolDoctor of Philosophy - PhD Computer Science, Doctor of Philosophy - PhD Computer Science at Columbia University
English, Korean, French
Github Skills (6)
pytorch10
python10
machine-learning-models10
documentation10
sphinx9
deep-learning9
Programming languages (6)
Github contributions (5)
scverse/scvi-tools
Aug 2021 - Oct 2022
Deep probabilistic analysis of single-cell and spatial omics data
Role in this project:
Back-end Developer & Documentation Specialist
Back-end Developer & Documentation SpecialistContributions:239 reviews, 117 commits, 149 PRs in 1 year 2 months
Contributions summary:Justin primarily focused on improving the documentation and formatting of the project. They made several commits related to fixing formatting issues within Sphinx galleries and adding margin-bottom to code blocks and paragraphs to improve readability. Furthermore, the user made a significant code contribution by implementing an LDA model within the scvi-tools framework, which involved writing a new module, including model and guide PyroModules. They also corrected a distribution mean, contributing to the enhancement of the model.
hierarchicaldeep-generative-modelmixture-of-expertssingle-cell-rna-seqsingle-cell
justjhong/minimal_personal_site
Dec 2016 - Nov 2021
Contributions:2 PRs, 61 pushes, 5 branches in 4 years 11 months
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