• Teaching Philosophy

I guide students to ask and answer the question, “Why does this matter?”. 

By helping them connect statistical and data‑driven concepts to real‑world relevance, 

I foster deeper understanding and ownership in learning.

• Teaching Experience  

1. Undergraduate Courses

- Introduction to Statistics 

- Exploratory Data Analysis (using Python)

- Design of Experiments (within the potential outcome framework for causal inference)

- Multivariate Data Analysis

- Clustering Analysis (covering both distance-based and model-based clustering)

- Data‑Driven Design Thinking (focusing on data‑informed decision-making)

2. Graduate Courses

- Advanced Statistical Inference (with latent variables)

- Advanced Design of Experiments (within the potential outcome framework for causal inference)

- Generalized Linear Models (including robust regression and cluster-weighted modeling)

• What Students Say :