Donghoon Lee
Director Of Single Cell Neurogenomics Group at Icahn School of Medicine at Mount Sinai
New York, New York, United States
Summary
👤
Senior🎓
Top SchoolDonghoon Lee is a computational biologist and machine learning-driven neurogenomics leader with over a decade of experience translating single-cell multiomics into target prioritization and precision medicine for Alzheimer’s disease. As Director of the Single Cell Neurogenomics Group and Assistant Professor at Mount Sinai, he integrates interpretable ML, QTL mapping, and immune–brain interactome studies to illuminate protective and neuroinflammatory mechanisms. Trained at Yale (Ph.D.) with prior cancer genomics and biomedical engineering roots, he blends rigorous academic research with practical software and data-engineering skills—evidenced by contributions to the tflearn deep learning library. His interdisciplinary background, spanning NIH-quality bioinformatics QA to clinical sequencing pipelines, enables him to move complex functional genomics from algorithm to biological insight.
10 years of coding experience
12 years of employment as a software developer
Doctor of Philosophy (Ph.D.), Computational Biology and Bioinformatics (CBB), Doctor of Philosophy (Ph.D.), Computational Biology and Bioinformatics (CBB) at Yale UniversityMaster of Science - MS, Biomedical Engineering, Master of Science - MS, Biomedical Engineering at Washington University in St. LouisThomas Jefferson School
English, Korean
Github Skills (8)
neural-network10
machine-learning10
lstm10
deep-learning10
tensorflow10
python10
nlp9
data-science8
Programming languages (6)
Github contributions (5)
tflearn/tflearn
May 2016 - May 2016
Deep learning library featuring a higher-level API for TensorFlow.
Role in this project:
ML Engineer
ML EngineerContributions:5 commits, 4 PRs, 2 comments in 5 days
Contributions summary:Donghoon contributed to the `tflearn/tflearn` repository by modifying example code and addressing specific issues within the library. Their work involved updating LSTM-related examples, fixing SSL issues with URL calls, and converting city names to lowercase. They also addressed a deprecated argument in TensorFlow and corrected a potential typo, demonstrating an understanding of the library's functionalities and dependencies.
apidata-sciencedeep-learningmachine-learningdeep-learning-library
leelaboratory/leelaboratory.github.io
Jul 2020 - Oct 2023
Contributions:45 pushes, 1 branch in 3 years 4 months
Find and Hire Top DevelopersWe’ve analyzed the programming source code of over 60 million software developers on GitHub and scored them by 50,000 skills. Sign-up on Prog,AI to search for software developers.