Teaching that Leaves a Trace

01Context: statistics as a decision craft

Most students meet statistics as a pile of procedures. The risk is that they can run a model and still cannot say what the result is allowed to claim. My teaching appointment is built around closing that gap — especially in time series, probability, and forecasting courses where dependence and uncertainty are easy to understate.

Teach the decision, not only the formula.

02Courses I keep returning to

Recent and recurring courses include:

• Time Series / Time Series Analysis / Advanced Time Series Analysis — core and advanced cohorts
• Probability & Statistics I / II — foundations for SDS undergraduates
• Forecasting and Predictive Analytics — small seminars focused on judgment under uncertainty
• AI Exploration I — connecting curiosity about AI with disciplined statistical thinking
• Survival Modelling, Statistical Capstone, Statistical Modelling in Financial Markets — applied judgment under different data regimes

03Program and advising as teaching infrastructure

Since 2015 I have served as Program Coordinator for Statistics. Current and recent leadership includes Director of Academic Advising (Statistics; previously Financial Engineering), Chair of the UG student organization committee in SDS, Curriculum Committee, School Board, and Admission Committee for the Master of Financial Engineering.

I also supervised Wei Dai’s PhD (2016–2021) on statistical inference and prediction evaluation in martingale regression models.

04What comes next

As Co-PI on AI-powered personalized learning (2025–2027), I am actively studying how AI can enhance teaching and learning in statistics — supporting practice and feedback without replacing the teacher’s role.

Contact me →