Jiadong Lin
Postdoctoral Researcher at University of Washington
Seattle, Washington, United States
Summary
👤
Senior🎓
Top SchoolJiadong Lin is a postdoctoral researcher in Seattle with a decade of experience at the intersection of machine learning and computational genomics, focused on algorithms for structural variant detection and variation/graph genomes. He combines deep learning for genomics and pathology images with classical methods like random forests, AdaBoost, and sequential pattern mining to tackle noisy biological and time-series data. His work spans academia and industry research projects—including algorithmic contributions that improved classifier AUCs by 2–7% during a University of Michigan collaboration—and bridges theory and practical tool-building in Python, C++ and Java/.NET. Trained with dual PhD affiliations and a strong CS and engineering foundation, he brings a rare blend of algorithmic rigor and hands-on systems programming to large-scale genomic variation problems.
11 years of coding experience
1 year of employment as a software developer
Doctor of Philosophy - PhD, Bioinformatics and Computational Biology, Doctor of Philosophy - PhD, Bioinformatics and Computational Biology at Leiden UniversityBachelor's Degree, Electrical and Electronics Engineering, Bachelor's Degree, Electrical and Electronics Engineering at Xidian UniversityDoctor of Philosophy, Bioinformatics and Computational Biology, Doctor of Philosophy, Bioinformatics and Computational Biology at Xi'an Jiaotong UniversityMaster's Degree, Computer Science, Master's Degree, Computer Science at Michigan State University
English, Chinese
Stackoverflow
1reputation
0reached
0answers
0questions
Github Skills (58)
structural-variation10
sequencing10
dotplot9
genome9
bioinformatics9
dna-sequences9
genomics9
graph8
next-generation-sequencing8
sequence-analysis7
nmf7
galaxy7
benchmarking7
deep-neural-networks7
deep-learning7
Programming languages (9)
Github contributions (5)
xjtu-omics/SVision
Feb 2021 - Nov 2022
Detecting genome structural variants with deep learning in single molecule sequencing
Contributions:13 releases, 98 commits, 93 pushes in 1 year 9 months
deep-learningsequencingstructral-variationsingle-molecule-sequencingdeep-neural-networks
jiadong324/Mako
Jan 2020 - Mar 2021
Contributions:1 release, 42 pushes, 1 branch in 1 year 2 months
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