Daniel Kim
Fellow at Memorial Sloan Kettering Cancer Center
New York, New York, United States
Summary
👤
Senior🎓
Top SchoolDaniel Kim is a physician-scientist and engineer who blends 10 years of experience across nanotechnology, synthetic biology, and electrical engineering to design novel biological systems and health solutions for resource-limited settings. Trained at MIT (EECS) and Stanford (MD/PhD, Biomedical Informatics) and now a fellow at Memorial Sloan Kettering, he moves fluidly between wet lab design, biointerface engineering, and computational pipelines. His open-source contributions include refining the widely used ENCODE ATAC-seq pipeline—improving fragment/peak calculations and multimapping read handling—which reflects a practical focus on accuracy and usability in bioinformatics. Past roles span clinical residency, nanoparticle therapeutics research, and product engineering at biotech startups, giving him uncommon depth in translating molecular tools into deployable systems. He is particularly adept at integrating organic–inorganic interfaces and circuit principles into biological design, with a track record of process improvements and automation in lab workflows.
10 years of coding experience
3 years of employment as a software developer
B.S., Electrical Engineering and Computer Science, B.S., Electrical Engineering and Computer Science at Massachusetts Institute of TechnologyMD/PhD, Biomedical Informatics, MD/PhD, Biomedical Informatics at Stanford University School of Medicine
Github Skills (13)
samtools10
bioinformatics10
pipelining10
python10
pipe10
pipeline10
data-analysis10
bash8
dockers5
wdl5
docker5
github-ci4
githubaction-workflow4
Programming languages (4)
Github contributions (5)
ENCODE-DCC/atac-seq-pipeline
Apr 2019 - Apr 2019
ENCODE ATAC-seq pipeline
Role in this project:
Bioinformatician & Software Engineer
Bioinformatician & Software EngineerContributions:7 commits, 2 PRs, 4 pushes in 17 days
Contributions summary:Daniel primarily focused on refining the ATAC-seq data analysis pipeline. Their contributions include bug fixes related to fragment length calculations and peak presence, and improvements to read count calculations, particularly addressing multimapping issues. They also updated documentation and HTML output to improve user understanding and point to relevant resources, showing a focus on accuracy and usability within the pipeline. The user also merged updates and refactored code.
pipelinefastaencodeatacseq
kundajelab/tronn
Dec 2016 - Aug 2021
Contributions:1 release, 1163 commits, 3 pushes in 4 years 8 months
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