Bio

I am a final year PhD student in MS&E at Stanford, with PhD Minor in Statistics. I am fortunate to be advised by Markus Pelger. As a member of the Advanced Financial Technologies Lab, I organize the lab’s Doctoral Seminar.

Research Brief

I develop statistical methods for inference in large dimensional data sets to make better decisions. My domain knowledge of financial economics problems informs my methodological work.

I identify a new class of multiple testing problems in panel data learning, which is broadly applicable. In a sequence of follow-up papers, I use this framework for latent graphs learning and change point detection in time-series.

See more in my research tab.

Updates

• [August 2024] Present panel inference in Econometric Society Interdisciplinary Frontiers Economics and AI+ML Meeting at Cornell.

• [May 2024] Present panel inference in 2024 Hong Kong Conference for Fintech, AI, and Big Data in Business at City University of Hong Kong.

• [Oct 2023] Present panel inference in INFORMS Session SE73, October 15 (Sun) in Pheonix, AZ.

• [July 2023] Change point detection accepted in ICML 2023 SPIGM and SCIS in Hawai’i.

• [June 2023] Present panel inference in AMES at SEM Tsinghua University 清华大学经管学院.

• [June 2023] Present panel inference in NASMES at UCLA.

• [May 2023] Co-organized and presented at AI in Fintech Forum.

• [Mar 2023] Present panel inference in 11th WCMF at UC Berkeley.

• [Oct 2022] Working paper on Cadeveric Organ Allocation project selected as Spotlight at NeurIPS 2022 Learning from Time Series for Health.

• [Oct 2022] Present the Cadeveric Organ Allocation project at INFORMS on Monday 11am see details here.

• [August 2022] Present panel inference at NBER-NSF SBIES: Session on Mixtures and Panel.

• [June 2022] Internship at Meta (previously Facebook), working on sentiment analysis and ads recommendation.

• [May 2022] Present panel inference at California Econometrics Conference.

• [April 2020] Advanced to PhD Candidacy.