Renyuan Xu Honored with Prestigious NSF CAREER Award

| June 3, 2024

An expert in harnessing probability for decision-making, Xu was selected for the National Science Foundation’s leading award for junior faculty.

Renyuan Xu

WiSE Gabilan Assistant Professor of Industrial and Systems Engineering Renyuan Xu. Image / Wei Ni

WiSE Gabilan Assistant Professor of Industrial and Systems Engineering Renyuan Xu has been recognized with the prestigious National Science Foundation (NSF) CAREER Award for 2024. The award honors early-career faculty members with the potential to serve as academic role models in research and education to lead advances in their respective fields. The NSF selects CAREER Award recipients who are building a firm foundation for a lifetime of leadership in integrating education and research.

Xu is an emerging research leader who harnesses machine learning and probability tools to improve decision-making in fields that experience a high degree of uncertainty, such as the financial and economic systems, or in public policy, such as the design of fair contracts and the allocation of social resources.

Xu’s CAREER Award project will concentrate on learning theory in large-scale stochastic games — complex systems that involve a large number of individuals making decisions under system uncertainties and complex information structures.

Xu said that one example of this process was in the financial markets. Financial systems usually involve many individual traders and institutional traders placing orders on different sides of the market to achieve their goals. Xu said her research aimed to understand the risk of financial networks and the behavior of individual participants, and to develop mechanisms to improve algorithmic trading efficiency and improve fairness.

“Another example is in e-commerce,” Xu said. “An e-commerce platform usually involves three parties: the owner of the platform, buyers, and sellers. A good mechanism ensures that buyers have access to accurate and effective information about the products, and also guarantees that the platform runs sustainably and offers fair contracts to the sellers.”

Xu said the research would also apply to large-scale transportation systems, such as making routing recommendations to ensure that traffic flows through the system with maximum efficiency and reduces overall congestion. She said that the CAREER Award project would look at improving the computational and learning efficiency of the platform to design better algorithms.

“For example, looking at the network structure in a transportation system — How could we utilize that structure to design decentralized algorithms to allow parallel computation?” Xu said.

“I believe that by improving our understanding of how to accelerate the computational process and enable more efficient learning algorithms, we could develop an almost real-time decision-making tool for numerous complex stochastic systems, such as transportation and e-commerce. It could make a huge influence,” she said.

The CAREER Award project will also involve an outreach element, where Xu will organize a summer school with colleagues from UC Santa Barbara and UC Berkeley. The summer school will offer a grounding to master’s and Ph.D. students interested in interdisciplinary work in this area so that they are better equipped to proceed with their research.

Xu joined the Daniel J. Epstein Department of Industrial and Systems Engineering in 2021 following a two-year role as a Hooke Research Fellow at Oxford University’s Mathematical Institute.

She completed her undergraduate studies in mathematics at the University of Science and Technology of China before moving to the U.S. for her Ph.D. at UC Berkeley in the Department of Industrial Engineering and Operations Research.

Xu was previously honored with the 2023 SIAM Activity Group on Financial Mathematics and Engineering Early Career Award and the 2022 JP Morgan AI Research Faculty Award.

Published on June 3rd, 2024

Last updated on June 3rd, 2024

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