Dr. Rui Wang | Data Science | Research Excellence Award

Rui Wang’s research advances intelligent energy systems with a strong emphasis on battery state estimation, data-driven diagnostics, and optimization frameworks for sustainable power applications. His work integrates artificial intelligence, probabilistic modeling, optimal control, and cyber-physical system design to enhance the reliability, safety, and efficiency of lithium-ion batteries and broader electrical infrastructures. Through contributions spanning battery State of Health estimation, extremum-seeking control for battery pack equalization, model-data fusion domain adaptation, and ensemble learning for confidence-aware diagnostics, he addresses critical challenges in renewable energy storage and intelligent transportation systems. His involvement in developing reinforcement learning architectures further strengthens the adaptability and optimization capacity of modern energy networks. With 4 research documents, 38 citations, and an h-index of 3, his published work reflects growing recognition within the energy systems, artificial intelligence, and control engineering communities. Collaborative projects with industrial partners highlight the practical relevance of his methods, particularly in implementing early-warning mechanisms for battery degradation and improving the reliability of next-generation electric mobility technologies. His research contributions collectively support the advancement of intelligent, sustainable, and data-driven energy ecosystems aligned with global technological and environmental priorities.