Dr. Wang’s research spans artificial intelligence (AI), mobile and edge computing, and efficient AI systems, with a focus on i) developing efficient learning algorithms and model architectures for large language models and multimodal AI, ii) designing adaptive AI systems through hardware-aware model optimization, runtime adaptation, and energy-efficient resource management, and iii) enabling AI applications in autonomous driving, AR/VR, and human-robot teaming. His research connects advances in AI models with practical deployment, aiming to make intelligent systems more capable, responsive, and sustainable under real-world resource constraints. Dr. Wang has had over 45 publications in his fields, including ICML, ICLR, EMNLP, ICDM, IEEE INFOCOM, ACM/IEEE SEC, IEEE SECON, ACM HotMobile, IEEE TMC, IEEE COMST, IEEE T-IV, IEEE TVT. He is also a co-inventor on 12 granted U.S. patents. His group’s work was recognized as a Best Paper Finalist at ACM/IEEE SEC 2025. Dr. Wang has served as an associate editor of Springer Multimedia Tools and Applications and IEEE Internet of Things Journal; a guest editor of ITU Journal Future and Evolving Technologies and MDPI Electronics; an organizor/TPC of international conferences in his fields such as IEEE INFOCOM, IEEE ICDCS, ACM e-Energy, ACM/IEEE SEC, AAAI, ACM HotMobile, IEEE MOST, IEEE MASS, ICCCN, IEEE VNC. He received the IEEE INFOCOM 2026 Distinguished TPC Member recognition.