Khôi Munchic is a data scientist specializing in cheminformatics with nine years of experience applying machine learning to drug discovery and proteomics. Raised in Vietnam and Russia and now based in Toronto, he brings a multicultural perspective to collaborative research teams at organizations like Terray Therapeutics and the Broad Institute. His background spans transcriptomics and proteomics to small-molecule modelling, pairing a data-science and biology bachelor's from Minerva with applied mathematics training from HSE. Known as a kind problem-solver on GitHub, he focuses on computational biology challenges that translate academic methods into production-ready pipelines. Khôi’s work blends hands-on model development with domain-aware feature engineering, often bridging experimental and computational teams. He’s equally comfortable prototyping ML architectures and integrating them into drug-discovery workflows, making him a pragmatic contributor in interdisciplinary settings.
9 years of coding experience
6 years of employment as a software developer
Bachelor's degree Data Science and Biology, Bachelor's degree Data Science and Biology at Minerva University
Bachelor's degree Applied Mathematics, Bachelor's degree Applied Mathematics at Higher School of Economics
High School Physics, High School Physics at Bauman Moscow State Technical University
This is the modified version of Pysam, a Python module for reading and manipulating SAM/BAM/VCF/BCF files. This implementation enables reading block-level symmetric-key encrypted BGZF files functionality.
Contributions:9 PRs, 85 pushes, 7 branches in 14 days
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