University of Wisconsin–Madison, Department of Agricultural and Applied Economics (2023–2026)
AAE 722: Machine Learning in Applied Economic Analysis (graduate course; Fall 2024, Fall 2025)
This course bridges econometrics and modern machine learning for economic and policy analysis with large datasets. Students get hands-on practice with Python, GitHub, and generative AI (GenAI) tools. Main text: An Introduction to Statistical Learning with Applications in Python (James, Witten, Hastie, and Tibshirani).
Section I. Foundations: statistical learning, linear regression, and classification
Section II. Model selection and regularization: cross-validation and the bootstrap, ridge and lasso, nonlinear models (splines and generalized additive models), and post-selection inference for high-dimensional data
Section III. Advanced methods: tree-based methods (random forests and boosting), support vector machines, and neural networks
Section IV. Further topics: survival analysis, unsupervised learning (principal components and clustering), and multiple testing
Section V. Applied practice: weekly Python labs, AI-assisted coding with GenAI tools, version control in GitHub, and a group final project (proposal, presentation, and report) that applies machine learning to a real economic or policy question
AAE 625: Agribusiness Economics and Management (Spring 2024, Spring 2025, Spring 2026)
This course covers managerial economics for agribusiness, combining economic theory with data analytics in Python, SQL, and Tableau.
Section I. Managerial economics: profit maximization, cost minimization, and market structure
Section II. Marketing and consumer behavior: segmentation, demand elasticity, regression, and A/B testing
Section III. Financial management: financial statements, ratios, and investment decisions
Section IV. Financial markets: credit, loan pricing, and default prediction
Section V. Supply chain management: logistics and distribution from farm to market
AAE 419: Introduction to Agricultural Finance (Spring 2024, Spring 2025, Spring 2026)
This course covers financial management for agricultural businesses, with hands-on financial modeling in Excel.
Section I. Financial statement and ratio analysis
Section II. Time value of money
Section III. Investment analysis and capital budgeting (NPV and IRR)
Section IV. Risk management
Section V. Agricultural credit markets
AAE 350 & NUTR SCI 350: World Hunger and Malnutrition (Summer 2024, Summer 2026)
An interdisciplinary course on hunger and malnutrition in developing countries and the United States, cross-listed with Nutritional Sciences, Agronomy, and CALS. The course has two parts: the biology and physiology of malnutrition, and its socio-economics and policies. I lead the second part, which applies economic analysis to world hunger. Main text: The World Food Problem (Leathers and Leonard, 6th edition).
Section I. Food security: the Sustainable Development Goals, food security, and famine
Section II. Food markets: supply and demand, markets, prices, and international trade
Section III. Food production: inputs, technology, and the Green Revolution
Section IV. Income and households: economic growth, income, purchasing power, and household food and nutrition
Section V. Shocks to food systems: COVID-19, environment and climate change, and war
Section VI. Anti-hunger policy, and a final project on a real-world food security problem
AAE 724: Practicum for Applied Economists (every semester, Fall 2023–Spring 2026)
Students carry out individual research projects that apply quantitative analysis to real-world problems, from framing a research question and preparing data to analysis and a professional report and presentation.
AAE 899: AAE Graduate Practical Training/Internship (every semester, Fall 2024–2026)
Hands-on work with industry partners, where graduate students apply what they learned in their coursework to real business problems. Students take one of two tracks under my supervision.
Internship: students work off-campus at a company or organization, guided by an industry supervisor, ideally leading to full-time employment after graduation. My students have interned at companies such as Foxconn.
Practical training: student teams work on campus on a real project submitted by an industry partner, with a contact person at the partner organization.
Progress: weekly progress reports to me, plus progress reports from the industry partner or site supervisor.
Final deliverables: an individual written report and a professional presentation to the partner, with recommendations to improve the firm’s financial performance, staffing efficiency, risk management, sustainability, or market competitiveness.
AAE 990: Research and Thesis (independent study; Summer 2026)
Independent research and writing that graduate students complete for their thesis or dissertation requirement, under my supervision. I guide each student through the full process, from shaping the research question and building the analytical framework to analyzing the data and writing the thesis.
AAE 999: Special Work in Agricultural and Applied Economics (independent study; every semester, Spring 2024–Summer 2026)
Directed study projects that each graduate student arranges one-on-one with me. I tailor every project to the student’s career goals, whether they are heading into industry or a Ph.D. program.
Course AEM 4070 & AEM 6070: Advanced Financial Analytics
- This course was a combination of traditional lectures and lab sessions. Students enhanced their employability and competitiveness in the job market by developing hands-on modeling and programing experiences.
- Section I. Data management using SQL
- Section II. Data modeling using MATLAB
- Section III. Python for finance: Introduction to Python and machine learning
- Section IV. In class lab sessions to develop data and analytics products
Course AEM 4041: Introduction to Credit and Banking
- This course provided students a general overview of the credit markets, the economic functions of banks, and credit analysis. Quantitative analysis, business analytics, and SAS programming skills were also incorporated into this course.
- Section I. Introduction and overview of bank, bank function and regulations
- Section II. Quantitative analysis: interest rates estimation, loan and credit risk analytics
- Section III. Case analysis and interpretation: bank management simulations and competitions.
Course AEM 2050: Introduction to Agricultural and Development Finance
- This course introduced an overview of the fundamentals of finance and its applications in agricultural economics.
- Section I. Financial statements
- Section II. Cash flow projections for various scenarios
- Section III. Risk management in agriculture
- Section IV. Time values of money and investment decisions
- Section V. Financial analysis
Texas A&M University, Department of Agricultural Economics, Market and Information Economics (Teaching Assistant, 2012–2013)
■ Course AGEC 105: Introduction to Agricultural Economics
■ Course AGEC 314: Food Marketing
■ Course AGEC 317: Economic Analysis for Agribusiness and Management
■ Course AGEC 413: Agricultural Cooperation
■ Course AGEC 440: Agribusiness Strategy Analysis
■ Course AGEC 622: Simulation and Forecasting
■ Course AGEC 5010: Farm Management and Finance