Teaching

“If you want to master something, teach it.”
- Richard Feynman

I owe a lot to the wonderful teachers and mentors I’ve had over the years—not just in math. One of my English professors helped convince me to do a PhD!

I really appreciate the chance to share ideas with students. Teaching is rewarding, and I usually come away understanding the material a little better myself.

Course design: Understanding Uncertainty

I recently designed and taught Understanding Uncertainty, an introductory statistics and data science course. Instead of starting with a lot of formal machinery, it leans on sampling and programmatic simulation to help build intuition.

The course site includes lecture materials and assignments.

Preview of the Understanding Uncertainty course website — Understanding Uncertainty course website

Teaching at Wharton

Students attending a STAT6130 lecture — STAT6130 lecture

I have taught and supported courses across regression, data science, sports analytics, and data collection. I have served as a teaching assistant for:

STAT6130: Regression Analysis for Business (MBA)
STAT4730: Data Science with ChatGPT (Undergraduate/MBA)
STAT4010: Sports Analytics Capstone (Undergraduate)
STAT4100: Data Collection and Acquisition (Undergraduate/MBA)
Moneyball Academy [High School]

I received the 2026 Donald S. Murray Prize for Excellence in Teaching from Wharton’s Statistics and Data Science Department, and I hold a teaching certificate from the University’s Center for Excellence in Teaching, Learning, and Innovation (CETLI).

Earlier, I tutored undergraduates in physics and data science.