Darvesh Gorhe is a PhD candidate in Biological Sciences at Columbia University with eight years of experience blending software engineering, data science, and computational biology. Trained in MS Data Science at Columbia and BS Neuroscience at UC San Diego, he has built ML and MLOps pipelines—applying graph neural networks and convex optimization—to tackle problems like Alzheimer’s gene prioritization and proteomics network analysis. At Columbia he has been the primary computational lead in a lab, crafting bioinformatics pipelines and supporting experimentalists while pursuing independent research in in-silico cell simulations and quantitative high-throughput methods. Comfortable shipping production backend systems from serverless cloud functions to automated model training, he bridges rigorous statistical inference with scalable engineering. He aims to translate computational biology research into industry impact and is open to collaborations that fuse molecular insight with data-driven discovery.
8 years of coding experience
3 years of employment as a software developer
University of California, San Diego
Master of Science - MS Data Science, Master of Science - MS Data Science at Columbia University
Contributions:67 commits, 4 PRs, 15 pushes in 18 days
imagescreenshot
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.