Grants and Contributions:

Grant or Award spanning more than one fiscal year. (2017-2018 to 2022-2023)

The e-commerce is one of the fastest growing sectors in global economies. At an extraordinary speed, it is boosting market efficiency, releasing underutilized productive forces, and expanding the markets. Two pillars are at the base of this epoch-making development: computational powers and market innovations. These two lend support and pose challenges to each other, creating a burgeoning interdisciplinary area between Computer Science and Economics. My research in Algorithmic Game Theory aims to contribute results and train students to push the frontiers both in computational methods for solving economic problems and in innovative market design that can find applications in Internet marketplaces.

The first focus of the project is on designing and analyzing robust market mechanisms in complex environments. Non-traditional pricing mechanisms, such as large-scale frequent auctions and dynamic pricing, are salient features in major Internet marketplaces. Besides computational challenges to optimize such mechanisms, also crucial is their robustness, both in their reaction to observed market data and in incorporating strategizing on the part of the market participants. Building on my existing work that successfully applies approximation algorithm techniques to tackle problems in market design, I plan to further combine techniques from machine learning to enhance theoretical understanding on these mechanisms.

My second focus is on economic and computational problems arising from marketplaces known as platforms. Platforms enable transactions between two other groups of agents, typically enjoying an economy of scale across the two sides. Amazon's third-party market, Uber and Airbnb are some such examples; they are playing an increasingly important role in the e-commerce. Some of my existing work pioneers in understanding design issues in such markets, and a course I taught at Caltech is among the first to focus on these markets. In an ongoing project, I collaborate with a startup company to understand the matching mechanisms on platforms and the phenomenon of algorithmic pricing in these markets. The success of such projects not only could inform the design of platforms, but may also provide insights that help shape public discussions on these markets.

Besides the immediate impacts this work could have within the research community and on the industry, this research will provide key training to graduate and undergraduate students. It will produce highly-qualified personnel with skills and experience in reasoning computational systems armed with economic insights. These skills will prove to be a major asset in the expansion of Canada's growing knowledge-based economy.