Summary
Qiang Chen is an instructor and computational neuroscientist in Seattle with a decade of experience at the interface of biology and AI, specializing in mathematical modeling, electrophysiology, and functional imaging. His PhD training and cross-disciplinary education—from theoretical physics to entrepreneurship—drive bio-realistic models and experimentally grounded computational studies of retinal circuits. At the University of Washington he has led multiple projects that reverse-engineer photoreceptor transduction, dissect pathway-specific light adaptation, and reveal synaptic mechanisms shaping visual encoding, translating model invertibility into stimulus design. He combines high-performance computing and hands-on electrophysiology to connect single-cell biophysics with population-level retinal responses, informing potential non-invasive diagnostics. Beyond publications and conference talks, he brings an uncommon blend of theoretical rigor and practical lab skills that enables hypotheses to move quickly from code to experiment.
10 years of coding experience
B.S, Theoretical Physics, 3.75, B.S, Theoretical Physics, 3.75 at University of Science and Technology of China
Doctor of Philosophy (Ph.D.), Computational Neuroscience, 3.8, Doctor of Philosophy (Ph.D.), Computational Neuroscience, 3.8 at University of Chicago
Entrepreneurship studies, Entrepreneurship studies at The University of Chicago Booth School of Business
Ph.D student, Biology, General, Ph.D student, Biology, General at Northwestern University
Bachelor of Arts - BA, Engineering Physics/Applied Physics, 3.8, Bachelor of Arts - BA, Engineering Physics/Applied Physics, 3.8 at The Hong Kong Polytechnic University
English, Chinese