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Xue earns NSF CAREER Award

10-04-2024

Assistant Professor Yexiang Xue earned an NSF CAREER Award for his proposed work titled, “Solving Beyond-NP Satisfiability Modulo Counting Problems with Guarantees Using NP Oracles”

Assistant Professor Yexiang Xue earned an NSF CAREER Award for his proposed work titled, “Solving Beyond-NP Satisfiability Modulo Counting Problems with Guarantees Using NP Oracles”

AI for Critical Decision-Making: Uniting Logic and Probability

Advancements in AI could be used to aid in decision-making. Algorithms that make fast, accurate, data-driven, and optimal decisions can make the difference between life and death in critical moments, such as in natural disasters. These decisions require both symbolic reasoning, used for well-defined, rule-based problems and statistical reasoning, which handles uncertainty.

Progress has been made in symbolic decision-making and statistical inference individually, but Yexiang Xue, assistant professor of computer science at Purdue University, recognized the need for a tool that combines them to optimize decision-making. 

This innovative research aims to solve high-stakes real-world challenges, such as disaster preparedness and infrastructure planning, where accurate decision-making can mean the difference between success and failure.

“The integration of symbolic and statistical AI was rooted in the two prevailing schools of thoughts of AI since its creation – one, symbolism, which believes AI can be solved using symbolic reasoning, and the other, connectionism, which leverages probabilistic predictions made by neural nets. This award will explore a new way to unite these two schools of thoughts,” said Xue.

Satisfiability Modulo Counting (SMC)

Xue’s research introduces a novel approach known as Satisfiability Modulo Counting (SMC). SMC merges two powerful methods: satisfiability solvers, which handle symbolic reasoning, and weighted model counting, a technique used in statistical reasoning. 

By combining these two methods, SMC provides tighter guarantees and more reliable results than previous approaches, making it particularly well-suited for applications where both precision and probabilistic reasoning are essential.

For example, in planning for disaster preparedness, SMC can help city officials determine the optimal placement of emergency shelters while ensuring that, with high probability, residents can reach safety during extreme weather events. This blend of logic and probability enables decision-makers to create plans that not only meet deterministic requirements but also account for uncertain, high-impact scenarios.

Xue’s research is expected to have broad applications beyond disaster preparedness, extending to fields such as game theory, operations research, and AI-driven social good projects. His research is poised to significantly advance the integration of symbolic and statistical AI.

“Our hope is that the extensions of classical satisfiability solvers a new modulo theory of weighted model counting will allow us to make data-informed decisions with confidence in a diverse set of domains,” Xue said. 

NSF CAREER Awards

NSF CAREER awards are the organization’s most prestigious awards given to junior faculty who embody the role of teacher-scholars through research, education and the integration of those concepts within the mission of their organizations. CAREER awards support promising and talented researchers in building a foundation for a lifetime of leadership. Receiving this award reflects this project’s merit of the NSF statutory mission and its worthiness of financial support.

Yexiang Xue is an assistant professor of computer science at Purdue University. His research interests include developing intelligent systems that tightly integrate decision-making with machine learning and probabilistic reasoning under uncertainty. Prior to coming to Purdue, he received his Ph.D. degree in the Department of Computer Science at Cornell University.

 

About the Department of Computer Science at Purdue University

Founded in 1962, the Department of Computer Science was created to be an innovative base of knowledge in the emerging field of computing as the first degree-awarding program in the United States. The department continues to advance the computer science industry through research. US News & Reports ranks Purdue CS #8 in computer engineering and #19 and #18 overall in graduate and undergraduate computer science. Additionally the program is ranked 6th in cybersecurity, 8th in software engineering, 13th in systems, 15th in programming languages and data analytics, and 18th in theory. Graduates of the program are able to solve complex and challenging problems in many fields. Our consistent success in an ever-changing landscape is reflected in the record undergraduate enrollment, increased faculty hiring, innovative research projects, and the creation of new academic programs. The increasing centrality of computer science in academic disciplines and society, and new research activities—centered around foundations and applications of artificial intelligence and machine learning, such as natural language processing, human computer interaction, vision, and robotics, as well as systems and security—are the future focus of the department. cs.purdue.edu 

Writer: Molly Walker, walke598@purdue.edu

Source: Yexiang Xue

Last Updated: Oct 3, 2024 5:16 PM

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