Zhiyi Huang, a Ph.D. student at the University of Pennsylvania, works in the area of economics and computation. He has published papers in forums such as FOCS, ICALP, RANDOM, SODA and APPROX. His research agenda comprises three main aims: (i) the development of a general method for converting approximation algorithms into truthful mechanisms for social welfare maximization, (ii) characterization and design of computationally efficient and truthful mechanisms that obtain near-optimal revenue for multidimensional problems, and (iii) exploration of connections between mechanism design and differential privacy, aiming to develop mechanisms that are both truthful and differentially private. Huang’s existing publications demonstrate progress on all three aims.

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Mathematics & Physical Sciences

The Mathematics and Physical Sciences division supports research aimed at advancing our understanding of fundamental questions in mathematics, physics and computer science. Through grants and collaborations, the division brings together researchers to pursue ambitious ideas, develop new approaches and foster scientific exchange.

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