+ Welcome!

mail_outline Email: melody.huang@yale.edu

Twitter: @melodyyhuang

I'm currently an Assistant Professor of Political Science and Statistics & Data Science at Yale. My research broadly focuses on developing robust statistical methods to credibly estimate causal effects under real-world complications.

Before this, I was a Postdoctoral Fellow at Harvard, working with Kosuke Imai. I received my Ph.D. in Statistics at the Unversity of California, Berkeley, where I was fortunate to be advised by Erin Hartman.


Recent News

  • [June 2025]
My paper with Zhongren Chen on generalizing complier average causal effects is now available on ArXiv (link).
  • [May 2025]
My paper with with Eli Ben-Michael, Matthew McHugh, and Luke Keele on sensitivity analysis for clustered observational studies is now available on ArXiv (link).
  • [Feb. 2025]
My paper with Tiffany Tang and Ana Kenney on estimating interpretable subgroups with causal distillation trees is now available on ArXiv (link).
  • [Dec. 2024]
My paper with Yi Zhang and Kosuke Imai on minimax regret estimation for generalizing heterogeneous treatment effects is now available on ArXiv (link).
  • [Sept. 2024]
My paper on a overlap violations in external validity is forthcoming in the Annals of Applied Statistics.

+ Research

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+ Teaching

Yale University

  • PLSC 500: Foundations of Statistical Inference (Fall 2024 - Present)
  • PLSC 503/S&DS 614: Causal Inference (Spring 2025 - Present)

University of California, Berkeley (Graduate Student Instructor)

  • STAT 232: Experimental Design (Spring 2023)
  • POLI SCI 236B: Quantitative Methodology in the Social Sciences (Spring 2022)

University of California, Los Angeles (Teaching Assistant)

  • STAT 100C: Linear Models (Spring 2019)
  • ECON 412: Fundamentals of Big Data (Spring 2019)