معرفی
Xuewu Dai is a Lecturer in the School of Electronic and Information Engineering at Northumbria University since 2013. He holds a PhD in Electrical and Electronic Engineering from the University of Manchester (2008) and prior roles as Research Associate at the University of Oxford (2011-2013) and University College London (2009-2011). His research focuses on advanced signal processing, control systems, and wireless communications, with applications in industrial IoT, sensor networks, and transportation systems. He has contributed to projects like wastewater monitoring, gas turbine testing, and EV charging optimization.
Key achievements include the Early Career Research Prize (SWIG UK) for industrial sensor system development. His work integrates cutting-edge techniques such as deep learning, Kalman filtering, and optimization algorithms to address challenges in smart infrastructure and energy efficiency.
Recent publications span topics like rail transit energy conservation, industrial time synchronization, and biosensing systems. He collaborates on projects like ROARS (CubeSats for space weather) and EVOLVE (EV charging optimization). His research emphasizes real-world applications in environmental monitoring, transportation, and smart grids.
