Papers
5
Total Citations
380
H-Index
4
About
Dalei Wu is a leading researcher at the intersection of cyber-physical systems, robotics, and intelligent energy management. His work is distinguished by pioneering contributions to reconfigurable battery systems, where his highly cited 2016 survey (247 citations) established foundational design principles for large-scale battery packs in electric vehicles, robotics, and smart grid storage. Wu has also made significant advances in robotic sensor networks for critical infrastructure, developing novel node localization techniques for underground pipeline inspection (107 citations)—work that enables accurate, real-time monitoring in GPS-denied environments. More recently, he has pushed the boundaries of autonomous sensing through edge computing and reinforcement learning, creating cognitive ground-penetrating radar systems that can adapt to changing subsurface conditions. His forward-looking survey on graph-based reinforcement learning for networked coordination (2025) is already shaping how multi-agent systems collaborate. Wu has also helped define the emerging field of Internet of Things for smart and connected health, serving as guest editor for a special issue that bridges wearable sensors, robotics, and digital health platforms. His research consistently demonstrates how intelligent coordination—whether of battery cells, robots, or learning agents—can unlock new capabilities in safety-critical and autonomous systems.
Research Focus
Key Achievements
Top Papers
- 1Reconfigurable Battery Techniques and Systems: A Survey247 citations · 2016
- 2Node Localization in Robotic Sensor Networks for Pipeline Inspection107 citations · 2015
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