Feichen Shen is a Principal AI/ML Engineer and Associate Professor based in San Diego with over a decade of experience applying NLP, LLMs, and graph machine learning to drug discovery and clinical informatics. He has led teams at Bristol Myers Squibb and Amgen to build large-scale knowledge graphs and hybrid NLP/LLM pipelines that translate biomedical data into actionable research insights. At Mayo Clinic he ran NIH-supported projects on rare disease differential diagnosis, organized national NLP challenges, and published top-journal work on network embeddings for infectious diseases. He combines deep academic rigor (AI/NLP PhD and postdoc in biomedical informatics) with product-focused delivery across AWS-deployed platforms and cross-industry collaborations. Notably, his research has compared and validated many GNN architectures on real cancer datasets, revealing practical model choices for translational biomedical problems.
11 years of coding experience
13 years of employment as a software developer
Doctor of Philosophy (Ph.D.) Computer Science, Doctor of Philosophy (Ph.D.) Computer Science at University of Missouri-Kansas City
Postdoc Biomedical Informatics, Postdoc Biomedical Informatics at Mayo Clinic Alix School of Medicine
Micro MBA, Micro MBA at University of California, San Diego - Rady School of Management
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