Troy, N.Y. – Computer scientist and social choice expert Lirong Xia, an assistant professor of computer science at Rensselaer Polytechnic Institute, has won a prestigious Faculty Early Career Development Award (CAREER) from the National Science Foundation (NSF) Division of Information & Intelligent Systems.
“We congratulate Lirong for this recognition of his potential as a young researcher at Rensselaer,” said Curt Breneman, dean of the School of Science at Rensselaer. “Dr. Xia’s research is developing computational tools that will improve our ability to make collective decisions. We are proud to have him as a colleague and we will look forward to the advances he will introduce in the coming years.”
The CAREER Award is given to faculty members at the beginning of their academic careers and is one of NSF’s most competitive awards, placing emphasis on high-quality research and novel education initiatives.
Xia will use the five-year $524,989 grant to investigate computational mechanisms that improve individual contributions to collective decision making processes – such as news rankings – including crowd-sourcing in the presence of online “noise answers.” The project draws on economics, statistics, and computation to expand the capabilities of social choice mechanisms to handle large numbers of alternative choices, to extract ground truth from aggregated preferences, and to address problems where individual agents might not be able to compare some alternatives or have incentive to misreport their preferences.
In contrast to classical social choice theory, which has mostly focused on the selection between a few (typically two) alternatives, the project proposes a rigorous study of a model for computational choice that can discern between thousands or even millions of alternatives.
Xia’s research is at the intersection of computation and a branch of economics known as “social choice,” which analyzes the use of individual preferences to reach collective decisions or social objectives. Applications of social choice theory include voting, allocation of tasks, and recommendation systems such as online product recommendations. In each of these cases, people may be asked to express their preferences as part of decision making. Xia is also interested in improving online ranking and recommendations systems, such as those used by Amazon and Netflix to point customers toward products they may like. An ideal system would produce accurate rankings and recommendations with minimal input.
Xia joined the faculty at Rensselaer in 2013, after serving as a postdoctoral scholar and NSF Computing Innovation Fellow at the Center for Research on Computation and Society at Harvard University. He received his bachelor’s degree in computer science and technology from Tsinghua University in China, and a master’s degree in economics and doctoral degree in computer science from Duke University.