Summary
Yi Zhu is a Machine Learning Engineer and PhD in Industrial Engineering from Northwestern University with eight years of experience applying statistical learning, sequential decision-making, and simulation to real-world problems. Currently at WeRide.ai, he builds learning-driven systems for autonomous driving and has prior experience training reinforcement agents, developing evaluation pipelines, and designing GAN-based anomaly detectors. His academic work spans stochastic modeling, efficient inference for reinforcement learning, and novel sequential stopping rules—published and presented in top simulation venues. Comfortable in Python and C++, he blends rigorous theoretical research with production engineering, having implemented NLP and trading-compliance components earlier in his career. Trained at Tsinghua and Columbia, he brings a strong mathematical foundation and a knack for turning asymptotic theory into practical algorithms. A less obvious strength is his pattern of bridging deep theory with applied system-building—moving ideas from proofs to simulators and ultimately to deployed ML pipelines.
8 years of coding experience
1 year of employment as a software developer
Master of Arts (M.A.), Statistics, 3.83/4.0, Master of Arts (M.A.), Statistics, 3.83/4.0 at Columbia University in the City of New York
Nanodegree, Self Driving Car, Nanodegree, Self Driving Car at Udacity
Bachelor of Science, Fundamental Science Program of Mathematics and Physics, 3.67/4.0, Bachelor of Science, Fundamental Science Program of Mathematics and Physics, 3.67/4.0 at Tsinghua University
Doctor of Philosophy (PhD), Industrial Engineering and Management Science, 3.86/4.0, Doctor of Philosophy (PhD), Industrial Engineering and Management Science, 3.86/4.0 at Northwestern University
English, Chinese