Teaching

Duke University

Instructor

• Master’s Virtual Math & Stat Bootcamp (Summer 2023)
  • Revamped lecture materials to adapt to the virtual format
  • Created over 20 pre-recorded videos on three learning modules [Introduction, Linear Algebra, Calculus, Probability]
• Master’s Math & Stat Bootcamp (Summer 2022)
  • Delivered five lectures (2-3 hours each)

Guest Lecturer

• STA 725 - Bayesian Health Data Science (Spring 2025)
  • Instructor: Samuel Berchuck
  • Developed and delivered two lectures on Scalable GPs [Lecture 1, Lecture 2]
• STA 440 - Case Studies (Fall 2019)
  • Instructor: Fan Li
  • Delivered one lecture on web scraping

Course Enhancement

• STA 602 - Bayesian Statistical Modeling (Summer 2023)
  • Instructor: Li Ma
  • Developed two new labs to better align with lecture materials
• STA 323 / 523 - Statistical Computing (Spring 2020)
  • Instructor: Shawn Santo
  • Enhanced the efficiency and flexibility of an R Shiny leaderboard for a prediction competition assignment, by developing functionality to read in submissions, validate inputs, flag errors, compute scores, and visualize both current and historical team performance

Teaching Assistant

• STA 602 - Bayesian Statistical Modeling (Spring 2025, Fall 2020)
  • Instructors: Alex Fisher (Spring 2025), Li Ma (Fall 2020)
• STA 832 - Multivariate Analysis (Fall 2023)
  • Instructor: Peter Hoff
• STA 732 - Statistical Inference (Spring 2023)
  • Instructor: Yuansi Chen
• STA 199 - Intro to Data Science (Fall 2022, Fall 2021) (Head TA)
  • Instructors: Elijah Meyer (Fall 2022), Alex Fisher (Fall 2021)
• STA 532 - Theory of Statistical Inference (Spring 2021)
  • Instructor: Surya Tokdar
• STA 360 / 602 - Bayesian Statistical Modeling (Summer II 2020)
  • Instructor: Olanrewaju Michael Akande
• STA 230 - Probability (Summer I 2020)
  • Instructor: Henry Kirveslahti