Han Yuan
ML Scientist at Calico Life Sciences
South San Francisco, California, United States
Summary
👤
Senior🎓
Top SchoolHan Yuan is an ML scientist and computational biologist with eight years' experience developing DNA sequence models to study gene regulation and disease, currently applying ML at Calico Life Sciences. Trained in the Leslie lab during a Ph.D. in Computational Biology and Medicine at Cornell, Han has blended NLP-inspired embedding methods and probabilistic k-mer models to improve transcription factor binding interpretation and in vivo prediction. He has also developed multitask learning approaches for cancer drug response and contributed ML-driven immunotherapy response work as an intern at IBM. Based in South San Francisco, he pairs deep academic rigor with practical impact—twice recognized with Calico awards—and brings a rare combination of biology, math, and software skills rooted in both research and production settings.
8 years of coding experience
1 year of employment as a software developer
Doctor of Philosophy (Ph.D.), Computational Biology and Medicine, Doctor of Philosophy (Ph.D.), Computational Biology and Medicine at Cornell UniversityBachelor’s Degree, Major in Biology and Mathematics, Minor in Computer Science, Bachelor’s Degree, Major in Biology and Mathematics, Minor in Computer Science at Washington University in St. Louis
English, Chinese
Github Skills (35)
single-cell-genomics10
convolutional-neural-networks10
hierarchical10
variational-autoencoder10
seq10
autoencoder10
tsne10
single-cell-analysis10
rna-seq10
sequential10
topological-data-analysis9
temporal-data9
probabilistic9
density-estimation9
motif8
Programming languages (3)
Github contributions (5)
hy395/NGS_scripts
Apr 2018 - Nov 2024
Contributions:12 pushes in 6 years 8 months
calico/scBasset
Aug 2021 - Apr 2022
Sequence-based Modeling of single-cell ATAC-seq using Convolutional Neural Networks.
Contributions:16 commits, 46 pushes, 6 branches in 7 months
sequencesingle-cell-atac-seqconvolutionalneural-networksconvolutional-neural-networks
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