• Graded assignments and exams for INDENG 164: Introduction to Optimization Modeling. • Graded assignments and exams for INDENG 242A: Machine Learning and Data Analytics.

• Participated in weekly workshops discussing topics such as Stephen Boyd’s Convex Optimization, Trevor Hastie’s Statistical Learning, and research papers in credit risk and theoretical econometrics. • Independently delivered paper presentations and led more than six teaching sessions. • Assisted Professor Jianhui Xie in research on variable selection using non- parametric models. • Implemented block gradient descent, Monte Carlo simulations, nonlinear programming, and cross-validation in MATLAB and processed datasets (overdue bills and payees) using Python.

• Implemented two quantitative strategies from scratch using Python, including data acquisition (corporate financial and stock data), labeling, processing, and developing screening and backtesting functions. • Constructed machine learning models, replicated strategies from Wind reports, contributed to FOF portfolio construction, and documented meeting summaries.