Xiaorui LiuView profile
Assistant Professor
Xiaorui Liu is an Assistant Professor in the Department of Computer Science at North Carolina State University's College of Engineering, where he joined the faculty in August 2022. He also holds a courtesy appointment in the Department of Electrical and Computer Engineering. His research focuses on large-scale machine learning, trustworthy artificial intelligence, and deep learning on graphs, with applications across various domains including networking, cybersecurity, manufacturing, biology, and healthcare. He has established himself as a leading researcher in graph neural networks and scalable machine learning systems. Dr. Liu's educational background includes: Ph.D. in Computer Science from Michigan State University (2022) M.S. in Computer Science from South China University of Technology (2017) B.S. in Computer Science from South China University of Technology (2015) Dr. Liu's research interests span several cutting-edge areas in artificial intelligence and machine learning. His primary focus is on developing scalable and trustworthy machine learning systems , with particular emphasis on graph neural networks, large language models, and robust AI. His work addresses fundamental challenges in large-scale optimization , distributed machine learning , and adversarial robustness . He explores how to make AI systems more reliable, efficient, and applicable to real-world problems across diverse domains including social networks, biological systems, and industrial applications. His research group is actively investigating how to integrate graph learning with generative AI, enhance model robustness against attacks, and develop efficient training methods for massive datasets. His recent publications demonstrate a clear trend toward integrating traditional graph machine learning with emerging AI paradigms, particularly large language models. His work spans both theoretical foundations and practical applications, with increasing focus on real-world deployment challenges. The research covers diverse subfields including robustness certification, efficient model training, and application-specific adaptations for domains like manufacturing, healthcare, and cybersecurity. Dr. Liu has received numerous prestigious awards recognizing his research excellence: NSF CAREER Award (2025) AAAI-2025 New Faculty Highlights National AI Research Resource Pilot Award (2024) ACM SIGKDD Outstanding Dissertation Award (Runner-up, 2023) Amazon Research Award (2023) NCSU Data Science Academy Award (2023) NCSU Faculty Research and Professional Development Award (2023) Chinese Government Award for Outstanding Students Abroad (2022) Best Paper Honorable Mention Award at ICHI (2019) MSU Cloud Computing Fellowship (2021) MSU Engineering Distinguished Fellowship (2017) Dr. Liu actively mentors students at all levels, currently advising multiple PhD and Master's students including Zhichao Hou, Weizhi Gao, Xingyue Shi, and Daniel Buchanan. His research is supported by significant funding from organizations including NSF, Amazon Research, Snap Research, and internal university grants such as the NCSU Data Science Academy seed grant and the Faculty Research and Professional Development Program. He is expanding his lab to address emerging challenges in AI safety, large-scale graph learning, and trustworthy foundation models, with plans to recruit additional PhD and Master's students for Fall 2025 and 2026. Dr. Liu leads the Network and Data Science research group at NC State, focusing on large-scale graph neural networks and trustworthy AI. The group collaborates with institutions including Oak Ridge National Laboratory and industry partners like Amazon. They have developed innovative approaches such as LazyGNN for efficient large-scale graph learning and ProTransformer for enhancing transformer robustness. The lab maintains strong connections with the broader research community through tutorials at major conferences and active participation in standard-setting research venues.
