Jing Li Joins Florida State University as Tenure-track Assistant Professor

As we bid farewell to the esteemed Dr. Jundong Li, who will be joining Florida State University as a tenure-track assistant professor from Fall 2024, his research group is eager to start a new chapter at this prestigious institution. A renowned expert in graph machine learning, trustworthy/safe machine learning, and large language models, Dr. Li's work has garnered significant attention globally.

Dr. Yushun Dong, a highly motivated Ph.D. student under the supervision of Dr. Jing Li at the University of Virginia (UVA), is looking forward to joining forces with Dr. Li at Florida State University. As part of his research endeavors, Dr. Dong has made significant contributions to various projects, including 'Toward 3D Graph Foundation Models for Molecular Property Prediction,' which was honored with the UVA Engineering Research Innovation Awards (RIA) as Principal Investigator.

Dr. Jing Li's research interests are multifaceted, spanning data mining and machine learning. His group's work is generously supported by prominent organizations such as the National Science Foundation (NSF), Department of Energy, Commonwealth Cyber Initiative, Jefferson Lab, JP Morgan, Cisco, and Snap. With over 150 publications in top-tier conferences like KDD, NeruIPS, ICLR, Dr. Li's research has had a profound impact on various fields.

Dr. Jing Li holds a Ph.D. degree in Computer Science from the University of Alberta (2014), a B.Eng. degree in Computer Science from Arizona State University (2019), and an M.Sc. degree in Software Engineering from Zhejiang University (2012). Prior to joining UVA, Dr. Li received his Ph.D. degree under the supervision of Dr. 'Name'. He is currently an Assistant Professor at the University of Virginia with appointments in the Department of Electrical and Computer Engineering, Department of Computer Science, and School of Data Science.

Dr. Li's research group at Florida State University will undoubtedly flourish under his guidance, and we wish him all the best as he embarks on this new chapter. His contributions to the fields of graph machine learning, trustworthy/safe machine learning, and large language models are expected to be instrumental in shaping the future of these disciplines.

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