Platforms and Internet market design

电子商务是全球经济中增长最快的行业之一。它正在以超乎寻常的速度提高市场效率，释放未得到充分利用的生产力，扩大市场。这一划时代的发展有两大支柱：计算能力和市场创新。这两者既相互支持，又相互挑战，在计算机科学和经济学之间形成了一个新兴的交叉学科领域。我在算法博弈论方面的研究旨在贡献成果，并培训学生在解决经济问题的计算方法和可以在互联网市场中找到应用的创新市场设计方面开拓前沿。*该项目的第一个重点是在复杂环境下设计和分析稳健的市场机制。大规模频繁拍卖和动态定价等非传统定价机制是主要互联网市场的显著特征。除了优化这类机制的计算挑战之外，同样关键的是它们的健壮性，无论是在它们对观察到的市场数据的反应方面，还是在纳入市场参与者的战略方面。在我现有工作的基础上，我成功地将近似算法技术应用于解决市场设计中的问题，我计划进一步结合机器学习的技术，以增强对这些机制的理论理解。*我的第二个重点是由称为平台的市场产生的经济和计算问题。平台使另外两组代理商之间的交易成为可能，通常会在双方之间享受规模经济。亚马逊的第三方市场Uber和Airbnb就是这样的例子；它们在电子商务中扮演着越来越重要的角色。我现有的一些工作是理解此类市场中的设计问题的先驱，我在加州理工大学教授的一门课程是第一批关注这些市场的课程之一。在一个正在进行的项目中，我与一家初创公司合作，了解平台上的匹配机制以及这些市场中的算法定价现象。这些项目的成功不仅可以为平台的设计提供参考，还可以提供有助于塑造这些市场上的公众讨论的洞察力。*除了这项工作可能在研究界和行业内产生的直接影响外，这项研究还将为研究生和本科生提供关键培训。它将培养出高素质的人才，他们拥有推理计算系统的技能和经验，并拥有经济洞察力。这些技能将被证明是加拿大不断增长的以知识为基础的经济扩张的一项主要资产。

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.