معرفی
Dr. Daniel Dai is an Assistant Professor in the Department of Mathematics, Physics and Electrical Engineering at Northumbria University. His research focuses on advanced control systems, industrial IoT, and synchronization technologies. He holds a PhD awarded in December 2008. He is actively supervising PhD students and leading innovative projects in smart EV charging, reinforcement learning applications, and mission-critical IoT systems.
- Education: PhD (Awarded 2008)
His research interests include real-time synchronization protocols, fault-tolerant sensor networks, and AI-driven energy systems. Recent work emphasizes robust time synchronization for industrial IoT and dynamic scheduling algorithms for platoon systems. He has published extensively in top journals like IEEE Transactions on Industrial Informatics and IEEE Internet of Things Journal, with over 1700 citations.
Key projects include EVOLVE (EU-funded optimization of EV charging infrastructure) and ROARS (CubeSat-based atmospheric research). He collaborates internationally on topics like delay distribution management and chirp modulation sensors.
- Awards: None explicitly stated
Current grants include EU projects focusing on vehicular communications and space atmospheric studies. He advises on 4 core PhD topics: AI for EVs, reinforcement learning control, time synchronization, and platoon system co-design.
