Born in Huidong, China, Zhanlin identifies as a member of the Hakka sub-ethnic group, whose name translates to "guest families" in Mandarin due to their history of fleeing unrest during the Qing Dynasty. When Zhanlin was 12 years old, he immigrated to the U.S. with his mother, who worked as a cancer biologist at Vanderbilt University in Nashville, Tennessee. While volunteering in the Children’s Hospital at Vanderbilt University, he witnessed the passing of a little girl with brain cancer, which inspired him to pursue a future career in medicine.
After high school, Zhanlin attended Yale University and received a bachelor’s degree double majoring in Computer Science and Molecular, Cellular, Developmental Biology, and later earned a master’s degree in Statistics and Data Science funded by the NSF Graduate Research Fellowship. Outside of classes, Zhanlin worked with Professor Mark Gerstein on the ENCODE Consortium, using supercomputers to understand the meaning behind the human genome. He led numerous computational projects and is the first author of several publications in Bioinformatics, Nature Communications, and Science Advances. More importantly, he was also an active member of the Yale Concert Band and the Yale Bands Saxophone Quartet, where he played alto, tensor, and baritone saxophones.
During the gap year before medical school, Zhanlin interned at NASA's Jet Propulsion Laboratory in Section 347J Perception Systems working on machine learning-based navigation and path planning software for the Mars rover. Mentored by Shreyansh Daftry, Zhanlin published several conference articles, authored a textbook chapter on planetary rovers, and is named one of the primary inventors for his contributions to a patent at NASA.
Zhanlin is currently a medical student at Northwestern University Feinberg School of Medicine, where he holds leadership roles as co-president of the Digital Health and Data Science Interest Group and founding co-president of the Aerospace Medicine Interest Group. As a future doctor, Zhanlin’s motto is to bring supercomputing to the bedside, by identifying real-world clinical issues and using technology to solve the complex problems in medicine.
