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Hello! I am a PhD candidate in quantitative marketing at the University of Rochester.
My research uses causal inference, machine learning, structural modeling, and experimental methods to study choice frictions, their marketing remedies, and the marketing implications of LLMs.
Prior to starting my PhD, I worked in the insurance industry developing marketing experiments and targeting models. I received my B.S. from University of Wisconsin-Madison, where I majored in Statistics and Mathematics. I am on the 2026-2027 academic job market for a tenure-track position.
Outside of work, I love tennis, sci-fi, and karaoke!
Contact: khuang32@simon.rochester.edu
Publication
Kang Huang, Mitch Lovett, and Gretchen Helmke, "The Electoral Choice Context and Support for Democratic Norms", accepted at PNAS
Working papers
Kang Huang, Yufeng Huang, "Can Advertising Correct Risk Beliefs? Evidence from U.S. Flood Insurance", JMP
Kang Huang, Yufeng Huang, and Xiaoting Zheng, “Fair Crowd Funding Ranking Design”, reject and resubmit at Marketing Science
Kang Huang, Mitch Lovett, and Ron Sharchar, "Who Let the Dog Out? News Media Attention Stimulates Negative Political Advertising"
Works in progress
LLM Digital Twin (with Ali Goli, and Hangfeng He)
LLM Competition (with Zeyu Lou)
Spillover Calories (with Arina Tveleneva and Liyu Zhao)
Social Learning in Insurance Markets
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