Shiliang Zhang

Shiliang Zhang is a Postdoctoral Fellow at the University of Oslo working with the Networks and Distributed Systems research group. His research focuses on privacy preservation in smart grid and transactive energy management systems, including the Privacy preserving Transactive Energy Management (PriTEM) project. He teaches Energy Informatics and Artificial Intelligence for Energy Informatics courses while developing interactive visualization tools for Norwegian energy infrastructure.

His primary research areas encompass Smart Grid systems, Transactive Energy Management, and Privacy Preservation through Differential Privacy techniques. He applies Artificial Intelligence and Energy Informatics to address renewable energy integration challenges, grid resilience, and autonomous navigation systems. Recent work explores bionic data-driven approaches for underwater navigation and anomaly-resistant control mechanisms.

Publications from 2022-2025 reveal strong interdisciplinary focus on machine learning applications for energy systems and navigation. Key themes include privacy-preserving pricing schemes for smart grids, robust control under system uncertainties, and deep reinforcement learning for geomagnetic navigation. His work spans IEEE Transactions, SmartGridComm, and Mathematics journals with significant contributions to resilient energy infrastructure.

No scientific awards were mentioned in available sources.

Zhang has no listed advisees but actively contributes to the PriTEM project within Networks and Distributed Systems. His research leverages collaborations across energy informatics domains, evidenced by publications in high-impact venues and development of practical tools like Norway's energy consumption and solar panel distribution maps.

He operates within the Networks and Distributed Systems research group, developing interactive visualizations for Norwegian energy infrastructure including municipal energy consumption (May 2025), Oslo's solar panel distribution (April 2025), and national power lines (May 2025). His work bridges theoretical control systems with real-world energy applications through the PriTEM project.