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About

Zhishang Wang is a leading researcher at the intersection of artificial intelligence, blockchain technology, and smart energy systems, with a particular focus on electric vehicle (EV) integration. His work centers on developing intelligent frameworks for Virtual Power Plants (VPPs), which balance grid loads by coordinating distributed energy resources. Wang’s most impactful contribution is the AEBIS system—an AI-enabled, blockchain-based EV integration platform for smart grid power management—which has garnered 108 citations for its novel approach to secure, decentralized energy distribution. He has also advanced predictive analytics with a robust multi-stage power consumption prediction method for semi-decentralized EV networks (22 citations), enhancing grid stability through demand-side management. Additionally, Wang’s exploration of reconfigurable AI chips for smart energy management (17 citations) demonstrates his commitment to hardware-software co-design for urban sustainability. His research, often contextualized within European smart city initiatives like Hamburg’s, offers practical solutions for integrating EVs and mobile robots into energy systems. With over 147 total citations across his key works, Wang is shaping the future of resilient, AI-driven power networks.