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Yexiang Xue is an Associate Professor at Purdue University in the Department of Computer Science. His research bridges large-scale constraint-based reasoning optimization with state-of-the-art machine learning techniques to enable intelligent agents to make optimal decisions in high-dimensional uncertain real-world applications. Specifically, his work is focused on scalable and accurate probabilistic reasoning techniques, statistical modeling of data, and robust decision-making under uncertainty. His research addresses key problems in multiple scientific domains, including artificial intelligence, machine learning, renewable energy, materials science, crowdsourcing, citizen science, urban computing, ecology, and behavioral econometrics. Dr. Xue aims to develop cross-cutting computational methods with an emphasis on computational sustainability and scientific discovery.
Department of Computer Science, Purdue University • West Lafayette, IN
Teaching and conducting research in large-scale constraint-based reasoning and machine learning.
GRE is not required.