Feichen Shen, Ph.D, Famia
About Feichen Shen, Ph.D, Famia
Feichen Shen, Ph.D., FAMIA, is a Sr. Principal Scientist in Artificial Intelligence at Bristol Myers Squibb and an Associate Professor (adjunct) at Mayo Clinic, with over 11 years of experience in Machine Learning, AI, Data Mining, and Biomedical Informatics.
Current Roles at Mayo Clinic and Bristol Myers Squibb
Feichen Shen holds dual positions in leading healthcare and biotechnological institutions. As a Sr. Principal Scientist in Artificial Intelligence, R&D at Bristol Myers Squibb in San Diego, California, he focuses on advanced AI research and development. Concurrently, he serves as an Associate Professor (adjunct) in the Department of Artificial Intelligence and Informatics at Mayo Clinic in Rochester, Minnesota. These roles highlight his extensive expertise and active involvement in both academic and industry settings.
Professional Background
Feichen Shen has accumulated extensive experience over his career, having worked at notable institutions. He spent five years at Mayo Clinic as an Assistant Professor in the Department of Artificial Intelligence and Informatics. During 2015, he served briefly as a Biomedical Informatics Scientist. Earlier stints at Mayo Clinic included positions in 2013 and 2012 as a Biomedical Informatics Scientist in the Department of Health Science Research. Additionally, Shen held a four-year instructor role at the University of Missouri-Kansas City.
Educational Background
Feichen Shen's educational journey includes an array of prestigious institutions. He earned a Doctor of Philosophy (Ph.D.) in Computer Science from the University of Missouri-Kansas City. Shen furthered his training with postdoctoral studies in Biomedical Informatics at Mayo Clinic School of Medicine. Additionally, he completed a Micro MBA program at the University of California, San Diego - Rady School of Management.
Industry Research and Contributions
Feichen Shen's research contributions include the development of a biomedical query generator for colorectal surgery cases at Mayo Clinic, aimed at identifying post-surgical complications. His work also involves applying mutual information and decision tree methodologies to detect surgical site infections from clinical notes. Shen has published over 80 peer-reviewed journal and conference articles, reflecting his significant influence in fields such as Computer Science and Biomedical Informatics.
Achievements and Expertise
Feichen Shen is recognized as a Fellow of the American Medical Informatics Association (FAMIA). With more than 11 years of experience, his expertise spans Machine Learning, Artificial Intelligence, Data Mining, and Biomedical Informatics. His career is marked by significant leadership in R&D and business development within the healthcare and biotech sectors.