Artificial Intelligence Research
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The recent explosive growth in artificial intelligence (AI) and data mining demonstrates their vast potential to radically transform the norms and practices in every industry and every aspect of our society. Our department is advancing the state of the art in both fundamental algorithms as well as new algorithms to help users benefit from this revolution and provide new capabilities for the benefit of society.
AI Core Faculty
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Madhur Behl
Dr. Madhur Behl is an associate professor in the departments of Computer Science, and Systems and Information Engineering.
He conducts research in Robotics and Artificial Intelligence, and is the team principal of UVA's Cavalier Autonomous Racing team
Zezhou Cheng
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David Evans
For information about me and my research, please see my web page and research group blog.
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Farzad Farnoud
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Lu Feng
Matheus Venturyne Xavier Ferreira
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Ferdinando Fioretto
Ferdinando Fioretto works on machine learning, optimization, differential privacy, and fairness. He is a recipient of the Amazon Research Award, the NSF CAREER award, the Google Research Scholar Award, the Caspar Bowden PET award, the ISSNAF Mario Gerla Young Investigator Award, the ACP Early Career Researcher Award, and several best paper awards.
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Tom Fletcher
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Yangfeng Ji
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Yen-Ling Kuo
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Jundong Li
Li's research interests are generally in data mining and machine learning, with a particular focus on graph mining, causal inference, and algorithmic fairness. As a result of his research work, he has published over 100 papers in high-impact venues. He has won several prestigious awards, and his work is supported by NSF, JLab, JP Morgan and Cisco.
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Yu Meng
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Yanjun Qi
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Hongning Wang
Tianhao Wang
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Chen-Yu Wei
Chen-Yu Wei is an Assistant Professor in the Computer Science department at the University of Virginia. Previously, he was a Postdoctoral Associate at Massachusetts Institute of Technology and a Research Fellow at the Simons Institute. His research focuses on fundamental problems in interactive decision making and reinforcement learning.
Haifeng Xu
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Aidong Zhang
Aidong Zhang's research focuses on developing machine learning approaches to interpretable and fair learning, concept-based learning, federated learning, and generative AI. She also works on large language models for hypothesis generations for scientific discovery.
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Miaomiao Zhang
Professor Zhang completed her PhD in computer science at the University of Utah. She was a postdoctoral associate in the Computer Science and Artificial Intelligence Laboratory (CSAIL) at the Massachusetts Institute of Technology.
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