Changlong Wu

About

Changlong Wu is an assistant professor in the School of Electrical, Computing and Software Engineering at the University of Arizona. He received his PhD in electrical engineering from the University of Hawaii at Manoa. Prior to joining the University of Arizona, he served as a visiting assistant professor in the Department of Computer Science at Purdue University and as a postdoctoral research associate at the NSF Center for Science of Information (CSoI).

Education

• PhD Electrical Engineering, University of Hawaii at Manoa, 2021
• BE Computer Science, Wuhan University, 2015

Selected publications

• C. Wu, A. Grama, and W. Szpankowski. No Free Lunch: Fundamental Limits of Learning Non-Hallucinating Generative Models, ICLR 2025.
• C. Wu, Y. Wang, and A. Grama. A Theory of Fault-Tolerant Learning, ICML 2024 (Spotlight).
• C. Wu, J. Sima, and W. Szpankowski. Oracle-Efficient Hybrid Online Learning with Unknown Distribution, COLT 2024.
• C. Wu, A. Grama, and W. Szpankowski. Online Learning in Dynamically Changing Environments, COLT 2023.
• C. Wu, M. Heidari, A. Grama, and W. Szpankowski. Precise Regret Bounds for Log-loss via a Truncated Bayesian Algorithm, NeurIPS 2022 (Oral presentation).