Dr. Tong Zhang is a distinguished professor of Computer Science at the University of Illinois Urbana-Champaign, where he leads pioneering research in machine learning and artificial intelligence. Previously, he served as a professor at the Hong Kong University of Science and Technology and held significant research positions at major technology companies including Tencent, Baidu, Yahoo, and IBM. He earned his Ph.D. in Computer Science from Stanford University following his M.S. in Computer Science from the same institution and his M.A. in Computer Science and Mathematics from Cornell University. Dr. Zhang's distinguished career bridges academic excellence and industry innovation, establishing him as a leading authority in theoretical and applied machine learning.
Dr. Zhang's seminal research focuses on machine learning algorithms and theory, with particular emphasis on statistical methods for big data and their practical implementations. His recent contributions include groundbreaking work on large language models, notably the development of R-Tuning for instructing LLMs to recognize knowledge limitations and LM-Infinite for zero-shot extreme length generalization, both recognized with Outstanding Paper Awards at NAACL 2024. These innovations have positioned him at the forefront of efforts to enhance the safety, reliability, and capability of foundation models in artificial intelligence. His scholarly impact is evidenced by his status as a fellow of the American Statistical Association, IEEE, and Institute of Mathematical Statistics, alongside editorial service for leading machine learning journals and conferences.
As an influential educator, Dr. Zhang teaches advanced courses including Machine Learning, Deep Learning Theory, and specialized topics on ML Algorithms for Large Language Models, shaping the next generation of AI researchers through rigorous theoretical instruction. He actively explores the evolving relationship between humans and AI systems, frequently discussing the next decade of human-machine collaboration with thought leadership that bridges academic research and industry applications. His laboratory continues to address fundamental challenges in machine learning while anticipating future directions for trustworthy artificial intelligence systems, with ongoing research focusing on improving the safety of LLM foundation models. Dr. Zhang maintains an active research agenda that continues to set standards for theoretical rigor and practical impact in the rapidly evolving field of artificial intelligence.
