STATS 250 (Fall 2019): Introduction to Statistics and Data Analysis (Undergraduate level)
STATS 531 (Winter 2020): Analysis of Time Series (Masters level)
STATS 415 (Fall 2020 and Fall 2021): Data Mining and Statistical Learning (Undergraduate level)
STATS 426 (Winter 2021): Introduction to Theoretical Statistics (Undergraduate level)
STATS 510 (Fall 2022): Probability Distribution Theory (Undergraduate level)
STATS 426 (Winter 2023): Introduction to Theoretical Statistics (Undergraduate level)
STATS 610 (Fall 2023): Statistical Inference (PhD level)
STAS 511 & 611 (Winter 2024): Statistical Inference (Masters level) and Large Sample Theory (PhD level)
During my PhD, I have also had the opportunity to mentor the following fantastic undergraduate and master’s students.
Zehua Wang (Masters at MIDAS): On the Computational Complexity of Private High-dimensional Model Selection via Exponential Mechanism (Accepted at Neurips 2024). Next step: PhD in Computer Science at the University of Virginia.
Manheng Wang (Undergraduate Research Program in Statistics 2023): Private Distributed Lasso. Next step: SWDE at Meta, San Francisco, CA.