Jaswanth Yella is an applied machine learning researcher and data scientist with a Ph.D. in Computer Science and 11 years of experience building production-ready AI systems from biomedical graph transformers to consumer recommender and GenAI advisor bots. Currently at Sephora, he focuses on personalized product and content experiences, while his academic work at Cincinnati Children’s advanced large-scale heterogeneous graph neural networks for drug repositioning and multi-drug adverse event prediction. His background spans industry research internships and early-stage startups, where he shipped everything from time-series transformer hybrids to analytics dashboards and ad-delivery software. Jaswanth combines rigorous research methodology with practical engineering—evident in a deployed soft-sensing model that improved recall by over 12% in noisy, imbalanced datasets. Based in San Francisco, he bridges foundational ML research and product impact, often translating complex biomedical models into scalable solutions for real-world applications.
11 years of coding experience
9 years of employment as a software developer
Doctor of Philosophy - PhD, Computer Science, Doctor of Philosophy - PhD, Computer Science at University of Cincinnati
Jawaharlal Nehru Technological University Hyderabad
Contributions:5 commits, 5 pushes, 2 branches in 1 year 4 months
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