Zimu Zhou

Zimu Zhou is an Assistant Professor at Tsinghua University's School of Software, Department of Computer Science and Technology, specializing in federated learning, edge computing, and mobile systems. With an extensive publication record spanning from 2018 to 2025, Dr. Zhou has established themselves as a leading researcher in distributed machine learning systems.

Dr. Zhou's research focuses on federated learning systems, mobile AI optimization, and spatial data processing. Their work addresses critical challenges in distributed machine learning including data heterogeneity, communication efficiency, privacy preservation, and practical deployment constraints. Recent research has expanded into federated large language models and advanced personalization techniques for mobile environments.

Analysis of Dr. Zhou's publication trends reveals a strong emphasis on practical deployment of federated learning systems, with increasing focus on real-world applications in mobility, urban computing, and AIoT. Their work bridges theoretical advances with practical implementations, as evidenced by multiple publications in top-tier systems and AI conferences.

• Best Paper Award, MobiCom 2024
• ACM SIGSPATIAL Best Paper Honorable Mention, 2022

Dr. Zhou has supervised several PhD students who have become active contributors in the field, including Xiaochen Li, Sicong Liu, and Yexuan Shi. Their research has been supported by multiple grants focused on edge intelligence and privacy-preserving distributed learning. Current projects include federated reasoning with large language models and resource-efficient AIoT systems.

Dr. Zhou leads the Distributed Intelligence Lab at Tsinghua University, which focuses on building practical frameworks for decentralized machine learning across mobile and edge environments. The lab collaborates with industry partners to deploy federated learning solutions in real-world settings.