Summary
Qiao Zheng is a quantitative researcher with 11 years of cross-disciplinary experience at the intersection of AI, mathematical modeling, and high-performance software engineering. Currently at Qube Research & Technologies after a Harvard postdoc, she models neural population codes and reinforcement learning in the brain using Julia, Python and CUDA, bringing theoretical neuroscience into production-ready simulation and analysis. Her background spans applied deep learning for medical imaging (Inria), production-scale real-time bidding systems (MediaMath) and quantitative finance (Geode, BNP), giving her a rare combination of academic rigor and trading-grade engineering. Trained in applied mathematics and finance at École Polytechnique and MIT and with a PhD-level computer science foundation from Inria, she excels at turning complex mathematical ideas into efficient, testable code. Notably, she has repeatedly bridged domains—translating neural data decoding methods into scalable implementations that inform both neuroscience research and quantitative decision-making.
11 years of coding experience
5 years of employment as a software developer
Master’s Degree Finance, Master’s Degree Finance at Massachusetts Institute of Technology
Engineer's degree (equivalent to Master's degree) Applied Mathematics, Engineer's degree (equivalent to Master's degree) Applied Mathematics at École Polytechnique
Bac+2 classe préparatoire scientifique (preparatory class of science), Bac+2 classe préparatoire scientifique (preparatory class of science) at Lycée Louis-le-Grand
Doctor of Philosophy (Ph.D.) Computer Science, Doctor of Philosophy (Ph.D.) Computer Science at Inria (French National Institute for Computer Science and Applied Mathematics)
English, French, Chinese, Chinese