Summary
Chengxi Zang is an Assistant Professor in Population Health Sciences at Weill Cornell Medicine and a faculty member of the Institute of AI for Digital Health, bringing nine years of expertise at the intersection of AI, machine learning, and large-scale real-world health data. He develops advanced generative models, causal inference methods, graph neural networks, and predictive algorithms to produce robust, generalizable real-world evidence that tackles problems like Alzheimer’s, Long COVID, youth suicide, and women’s health while accelerating drug discovery. A Tsinghua PhD with multiple institutional excellence awards, his work appears in top medical and CS venues (Nature Medicine, Nature Communications, KDD, AAAI) and has won best-paper honors and industry adoption at organizations including Boehringer Ingelheim. Beyond publications, his algorithms and code have been integrated into commercial workflows and widely covered by major media, reflecting both academic rigor and real-world impact. An early network-science visiting scholar and participant in Tencent’s elite program, he combines deep theoretical grounding with translational collaborations across academia and industry.
9 years of coding experience
9 years of employment as a software developer
Bachelor of Science - BS, Computer Science, GPA 4.1/5, Rank 1st/100, Bachelor of Science - BS, Computer Science, GPA 4.1/5, Rank 1st/100 at Sun Yat-sen University
Doctor of Philosophy - PhD, Computer Science, Top 3 in CS, and top 70/2279=3% in THU, Doctor of Philosophy - PhD, Computer Science, Top 3 in CS, and top 70/2279=3% in THU at Tsinghua University