Summary
Yuanzhe Liu is a Scientist II and PhD candidate in Economics (expected June 2025) who blends computational economics, Bayesian inference, and machine learning to turn rich local data into actionable forecasts and policy-relevant insights. With eight years of experience, he led ML-driven forecasting and pricing projects at the UCSB Economic Forecast Project—building Shiny-style Python apps, mentoring interns, and producing region-specific employment and inflation models for Santa Barbara County. Skilled in Python, R, PyTorch, SQL, time series forecasting, and causal inference, he bridges rigorous academic training (PhD UCSB; MS UW–Madison; BS RIT & Beijing Jiaotong) with industry-scale implementation. Now based in Burlingame and joining Uber as Scientist II, he combines econometric depth with production ML experience—an unusual mix that helps translate advanced reinforcement learning and Bayesian methods into practical decision tools.
8 years of coding experience
Master of Science - MS, Econometrics and Quantitative Economics, Master of Science - MS, Econometrics and Quantitative Economics at University of Wisconsin-Madison
Bachelor's degree, Computational Mathematics, Bachelor's degree, Computational Mathematics at Rochester Institute of Technology
Bachelor's degree, Economics, Bachelor's degree, Economics at Beijing Jiaotong University
Doctor of Philosophy - PhD, Economics, Doctor of Philosophy - PhD, Economics at UC Santa Barbara