Teaching

I teach courses in machine learning, quantitative finance, and machine learning and causal inference.

• DATASCI 347, Machine Learning: Fall 2023, Spring 2024, Fall 2024, Spring 2025, Spring 2026, Fall 2026

• DATASCI 385, Quantitative Finance: Fall 2022, Spring 2023, Fall 2023, Fall 2024, Fall 2026

• DATASCI 385, Machine Learning and Causal Inference: Fall 2021, Spring 2022, Fall 2022

Mentoring

I mentor graduate and undergraduate researchers and advise honors thesis students.

Undergraduate Honors Thesis Advisees:

• Phoebe Pan (2026, co-first author of EMNLP’25, Findings of ACL’26 and Findings of EMNLP’26 papers, PhD at Yale)

• Zihan Liang (2026, co-first author of EMNLP’25, Findings of ACL’26 and Findings of EMNLP’26 papers, PhD at Duke)

• Tsebaot Shewarega (2025, researcher at MIT)

• Krystal Song (2024, Evercore)

• Hao Wang (2023, first author of a submitted paper on experimental design, PhD at Yale)

• Leah Gao (2022, Paylocity)

Undergraduate Honors Thesis Committee Members:

• Haoyang Cui (2024, MS at MIT), Tia Hu (2024, Citi), Zoe Ji (2024, PhD at Stanford), Judy Hao (2023, PhD at UT Austin), Echo Sui (2023, MS at Stanford), Yixiao Chen (2023, MS at Yale), Zhou Fang (2022, MS at Harvard), Katherine Wang (2022, MS at MIT), Ethan Feldman (2022, UJA-Federation of New York)

Undergraduate Researchers:

• Kevin Lee (2023, JD at Harvard), Francis Lin (2022, JD at Georgetown)