About me

Welcome to my website!

I am currently a postdoctoral associate in the Department of Biostatistics at Yale University, where I have the privilege of working with Prof. Laura Forastiere at Yale and Prof. Edoardo M. Airoldi at Temple University. I earned my Ph.D. in Decision Sciences from the Fuqua School of Business at Duke University, where I was fortunate to be advised by Prof. Alexandre Belloni. Prior to that, I obtained my M.A. in Statistics from Boston University, where I had the pleasure of being advised by Prof. Daniel Sussman and Prof. Konstantinos Spiliopoulos.

I will be on the job market this year and welcome opportunities to connect! Please feel free to reach out if you’d like to have a chat.

Research Interests

My research primarily focuses on causal inference under network interference. Specifically, I am interested in:

• Defining meaningful and interpretable estimands for spillover effects.
• Developing computational and interpretable estimators for both average and conditional spillover effects in large-scale settings.
• Designing adaptive estimators for spillover effects that effectively balance the bias-variance tradeoff.
• Developing algorithms to identify optimal treatment rules under network interference.
• Extending spillover effect estimation by incorporating complex settings alongside network interference, such as jointly addressing biased sampling and network interference.

Beyond these core areas, I am also exploring causal discovery for extreme events. On the applied side, I am particularly interested in leveraging causal inference methods to support social scientists and medical researchers in deriving robust and trustworthy conclusions for their research problems.

I’d be delighted to connect if any of these interest you!

News

• [Aug 2025] Our paper, “Structural causal models for extremes: An approach based on exponent measures,” co-authored with Shuyang Bai and Tiandong Wang, is now available on arXiv.

• [Jun 2025] Our paper, “Inward and Outward Spillover Effects of One Unit’s Treatment on Network Neighbors under Partial Interference,” co-authored with Edoardo M. Airoldi and Laura Forastiere, is now available on arXiv.

• [June 2025] I will present our work, “Design-Based Weighted Regression Estimators for Spillover Effects,” co-authored with Laura Forastiere and Edoardo Airoldi, at the Society for Epidemiologic Research (SER) 2025 Annual Meeting, as part of the session titled “Causal Inference: OASS.” The talk is scheduled for Wednesday, June 11, from 5:30–6:00 PM.

• [June 2025] I will present our work, “Design-Based Weighted Regression Estimators for Spillover Effects,” co-authored with Laura Forastiere and Edoardo Airoldi, at New England Statistics Symposium (NESS), as part of the session titled “Advances in Methodologies for Estimating and Leveraging Causal Effects Under Interference in Public Health Studies.” The talk is scheduled for Tuesday, June 3, from 1:20PM-2:50PM.

• [May 2025] Our paper, “Association of Antihypertensive Medication and Steatotic Liver Disease with Liver Fibrosis and Mortality among US Adults,” co-authored with Yu Wu, is now available on medRxiv.

• [May 2025] I will present our work, “Design-Based Weighted Regression Estimators for Spillover Effects,” co-authored with Laura Forastiere and Edoardo Airoldi, at ACIC 2025 during the Poster Session, scheduled for Wednesday, May 14, from 5:30–7:00 PM.

• [Mar 2025] The second version of our paper, “Neighborhood Adaptive Estimators for Causal Inference under Network Interference,” co-authored with Alexandre Belloni and Alexander Volfovsky, is now available on arXiv.

• [Mar 2025] Our paper, “Estimating Direct and Spillover Vaccine Effectiveness with Partial Interference under Test-Negative Design Sampling,” co-authored with Cong Jiang, Denis Talbot, and Mireille Schnitzer, is now available on medRxiv.

• [Mar 2025] I will be presenting our work, “Design-Based Weighted Regression Estimators for Spillover Effects,” co-authored with Laura Forastiere and Edoardo Airoldi, at ENAR 2025 in Session 50 — “It’s All About the Estimand — Asking the Right Questions to Best Inform Health Policy Decisions,” scheduled from 1:45–3:30 PM.