Teaching philosophy

From pre-college all the way to graduate-level courses, I always strive to teach in a way that the main takeaways reveal themselves as 'obvious' or at least natural in light of previous discussion (“If you can't explain it simply, then you don't understand it well enough” - Albert Einstein).

I seek to instill understanding, not mindless regurgitation, and for this I use plenty of simple examples and emphasize the bases of the topics under consideration: a solid foundation will get you further than you may think.

Lastly, effective teaching must be engaging, which informs my presentation style and priorities (as resources, chiefly, time, are limited).

University of Wisconsin-Madison [as Graduate TA / Co-Principal Instructor]

1. STAT 240 - Data Science Modeling, Teaching Assistant to Professor Wu, Fall 2023, Spring 2024

2. STAT 610 - Statistical Inference, Teaching Assistant to Professor An, Spring 2023 [Graduate course] - Slides

3. STAT 333 - Applied Regression Analysis, Teaching Assistant to Professor Wu, Fall 2022

4. STAT 340 - Data Science Modeling II, Teaching Assistant to Professor Wu, Spring 2022

5. STAT 311 - Introduction to Mathematical Statistics, Teaching Assistant to Professor An, Fall 2021

University of Wisconsin-Madison [as Academic Tutor to student-athletes]

1. MATH 112 - Algebra, Fall 2021, Spring 2022, Fall 2022

2. STAT 301 - Introduction to Statistics, Fall 2021

3. STAT 324 - Statistics for Engineers, Fall 2021

4. SOC 360 - Statistics for Sociology, Fall 2021

5. STAT 371 - Statistics for the Life Sciences, Fall 2021

6. PUBLHLTH 783 - Statistics for Public Health, Fall 2021 [Graduate course]

Barcelona Tech

6. Programming, B.S. Statistics, Teaching Assistant to Professor Fairen, Spring 2017

7. Probability and Stochastic Processes, B.S. Statistics, Teaching Assistant to Professor Delicado, Fall 2016