Manu Setty is an Assistant Professor and computational biologist with 12 years of experience modeling and integrating high-throughput genomics data, currently leading translational data science efforts at Fred Hutch in Seattle. He develops machine learning methods for representation and visualization of single-cell RNA-seq and performs integrative analyses across RNA-, DNase-, ATAC-, histone, and TF ChIP-seq datasets. His work bridges computational method development and experimental collaboration, evidenced by first-author papers in Nature Biotechnology, Nature Genetics, Nature MSB and PLoS Computational Biology. With a PhD in Bioinformatics and prior roles at Memorial Sloan Kettering, Columbia and industry at Celsius Therapeutics, he combines academic rigor with applied biotech experience. Notably, his research trajectory emphasizes creating interpretable representations that facilitate biological discovery rather than black-box prediction.
12 years of coding experience
3 years of employment as a software developer
PhD, Bioinformatics, Systems Biology, Machine Learning, PhD, Bioinformatics, Systems Biology, Machine Learning at Weill Cornell Medical College
MS, Computer Science - Computational Biology, MS, Computer Science - Computational Biology at Columbia Engineering
Bachelor of Engineering, Computer Science, Bachelor of Engineering, Computer Science at National Institute of Technology Karnataka
Contributions:2 reviews, 3 PRs, 3 pushes in 1 year 5 months
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