Zijian Liu

Zijian Liu is a researcher affiliated with New York University (School of Business), University of Electronic Science and Technology of China (School of Information and Communication Engineering), and other institutions. He specializes in Machine Learning and Non-Convex Optimization, with a focus on Stochastic Gradient Descent and Variance Reduction techniques.

His publications (e.g., ICLR 2025, ICML 2024, COLT 2023) address theoretical advancements in optimization under Heavy-Tailed Noise, Non-Asymptotic Convergence, and Shuffling Gradient Methods. He has collaborated extensively with researchers like Zhengyuan Zhou, Alina Ene, and Huy L. Nguyen.

His research trends highlight Stochastic Optimization and Machine Learning Theory, particularly in handling noisy and non-convex problems. He has no documented scientific awards or advisees listed in available records.