Summary
Weige Huang is a PhD candidate in Economics at Temple University and a Teaching Assistant with eight years of experience applying microeconometrics, finance, and machine learning to empirical research and instruction. Proficient in R, Python, Matlab, and Stata, he blends rigorous econometric theory with practical computational skills to analyze high-frequency and micro-level financial data. His academic training includes a summa cum laude master’s in Finance from Shenzhen University and a B.A.Sc., reflecting a strong quantitative foundation across disciplines. Based in Greater Philadelphia, he contributes to coursework and research that bridge methodological innovation and real-world financial questions. Beyond teaching, he maintains a personal website showcasing projects and reproducible code, signaling a commitment to transparent, reproducible research.
8 years of coding experience
Ph.D, Microeconometrics, Finance, Machine Learning, Ph.D, Microeconometrics, Finance, Machine Learning at Temple University
Bachelor of Applied Science (B.A.Sc.), Bachelor of Applied Science (B.A.Sc.) at Southern Medical University
Master's degree, Finance, summa cum laude, Master's degree, Finance, summa cum laude at Shenzhen University
Chinese, English