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University of Michigan School of Information


Yingzhi Liang

Yingzhi Liang



I am a doctoral candidate at the University of Michigan, School of Information. My research interests are behavioral and experimental economics, market and mechanism design. I design theoretically-based mechanisms to solve social problems and evaluate them using controlled lab and field experiments.

Traditional market design studies the allocation rules of marketplaces, institutions, and other economic environments by assuming individuals in these markets have unbounded rationality. Consequently, theoretical results from standard market design models may not hold in practice. I study individual behavior in markets without assuming bounded rationality, and optimize allocation rules based on actual behavior. I use economic theory, lab, and field experiments to solve incentive problems in different markets and workplaces, including school choice and college admissions, the gig economy, and cooperation in groups.

When possible I seek to test my hypotheses in the field. I am fortunate to work with field partners in designing and conducting large scale randomized field experiments, including the largest ride-sharing company in China: ​DiDi​, the non-profit micro-lending platform: ​​, and the personalized online education platform: ​ECoach​, and the interactive decision-making learning tool: ​MobLab Inc​.

I expect to graduate in April 2021. I am looking for tenure-track and post-doc positions in the following disciplines: Business Schools (Operations Management), Economics (Behavioral and Experimental Economics), and Information Schools (Data Science).

Dissertation title

Behavioral Market Design for Social Good

Fields of interest

Behavioral and Experimental Economics 
Market and Mechanism Design 
Data Science 
Causal Inference 
Gig Economy 
Social Network


B.S. in Mathematics, Fudan University 
Ph.D. in Information, University of Michigan (expected 2021)