Dr. Xiao Zhou was born in 1994. He received his Ph.D. degree in Engineering from Tongji University in 2020. From 2020 to 2022, he conducted postdoctoral research at Tsinghua University. In February 2023, he joined the Department of Municipal Engineering at the School of CivilEngineering, Hefei University of Technology, where he currently serves as an Associate Professor and Deputy Head of the Department. His research primarily focuses on leakage control, optimized design, and intelligent scheduling of water distribution networks (WDNs). In addition to his academic roles, he is amember of the IWA China Leakage Control Expert Committee.

Research Interests

My research focuses the transformative integration of artificial intelligence (AI) and data science with urban water systems engineering. I aim to develop next-generation intelligent systems for water distribution networks, with a core focus on leveraging machine learning, deep learning, and graph-based algorithms to solve fundamental challenges. My work specifically explores: AI-driven mechanisms for leakage detection and diagnostics through multi-feature fusion; graph neural networks and network embedding techniques for adaptive hydraulic state estimation and pressure sensor optimization; and deep learning models for pipe burst identification and localization. By treating water networks as dynamic, data-rich systems, I develop methodologies that enable predictive maintenance, intelligent scheduling, and enhanced operational resilience, pushing the boundaries of smart water management.

Representative publications

1. Zhou, Xiao; Guo, Shuyi; Xin, Kunlun; et al. Network embedding: The bridge between water distribution network hydraulics and machine learning, Water Research, 2025, 273: 123011. IF = 12.4

2. Zhou, Xiao; Man, Yacan; Liu, Shuming; et al. Leveraging multi-level correlations for imputing monitoring data in water supply systems using graph signal sampling theory. Water Research X, 2024, 100274. IF = 8.2

3. Zhou, Xiao; Wan, Xi; Liu, Shuming; et al. An all-purpose method for optimal pressure sensor placement in water distribution networks based on graph signal analysis. Water Research, 2024, 122354. IF = 12.4

4. Zhou, Xiao; Zhang, Juan; Guo, Shuyi; et al. A Convenient and Stable Graph-based Pressure Estimation Methodology for Water Distribution Networks: Development and Field Validation, Water Research, 2023, 233: 119747. IF = 12.4

5. Zhou, Xiao; Guo, Shuyi; Xin, Kunlunet et al. Maintaining the long-term accuracy of water distribution models with data assimilation methods: A comparative study, Water Research, 2022, 226: 119268 . IF = 12.4

6. Zhou,Xiao ; Liu Shuming ; Xu, Weiron; et al. Bridging hydraulics and graph signal processing: a new perspective to estimate water distribution network pressures. Water Research, 2022, 118416. IF = 12.4

7. Zhou, Xiao; Tang, Zhenheng; Xu, Weirong; et al. Deep learning identifies accurate burst locations in water distribution networks. Water Research, 2019, 115058. IF = 12.4

8. Zhou, Xiao; Xu, Weirong; Xin, Kunlun; et al. Self-Adaptive Calibration of Real-Time Demand and Roughness of Water Distribution Systems. Water Resources Research, 2018, 54(8), 5536-5550. IF = 5.0

9. Chen, Xinran; Zhou, Xiao*; Xin, Kunlun*; et al. Sensitivity-Oriented Clustering Method for Parameter Grouping in Water Network Model Calibration. Water Resources Research, 2022, 58, e2021WR031206. IF = 5.0

10. Xu, Weirong; Zhou, Xiao; Xin, Kunlun; et al. Disturbance Extraction for Burst Detection in Water Distribution Networks Using Pressure Measurements. Water Resources Research, 2020, 56(5), e2019WR025526 . IF = 5.0

Projects

National Natural Science Foundation of China (General Program)
01/2024 – 12/2027 | Role: Principal Investigator
Research on the Mechanism of Multi-Source Feature Fusion and Integrated Diagnostic Methods for Leakage in Water Supply Networks