Summary
Haiqing Z is an Assistant Professor at UTMB with a decade of experience at the intersection of AI, structural biology, and computational biophysics. Trained as a biophysicist (PhD, UMD) and with research stints at Columbia, Duke, and NCI, he builds machine learning and structure-based methods to predict protein–protein interactions and binding specificity at genome scale. His work blends multiscale molecular simulation, electrostatic energetics, and deep learning to connect mechanistic physical models with high-throughput interaction maps. He has a strong teaching record—designing undergraduate and outreach courses—and a history of translating simulation insights into experimentally relevant hypotheses about histone assembly and nucleosome dynamics. Based in Beijing with an international career, he brings both academic rigor and pragmatic tool-building to problems in structural systems biology. An underappreciated strength is his ability to fuse coarse-grained physics models with modern AI to reveal hidden sequence symmetries that drive folding and assembly.
10 years of coding experience
13 years of employment as a software developer
Master’s Degree, Physics, Master’s Degree, Physics at Michigan Technological University
Doctor of Philosophy - PhD, Biophysics, Doctor of Philosophy - PhD, Biophysics at University of Maryland