Prof. Maoguo Gong

IEEE Fellow, Inner Mongolia Normal University, Xidian University

Maoguo Gong is a Professor at Xidian University and Vice President at Inner Mongolia Normal University. He is an IEEE Fellow (2024) with research in computational intelligence, collaborative learning, optimization, and remote sensing. He has published 200+ papers, holds 30+ patents, and has an H-index of 76. He serves as Associate Editor for several IEEE journals and has received numerous national awards.

Prof. Jiajia Liu

IEEE Fellow, Northwestern Polytechnical University

Jiajia Liu is a full professor with the School of Cybersecurity, Northwestern Polytechnical University. He is the director of Shaanxi Provincial Engineering Laboratory of Cyber Security since 2021, and the director of Xi’an Unmanned System Security and Intelligent Communications ISTC Center since 2020. He was a full Professor at the School of Cyber Engineering, Xidian University, from 2013 to 2018. His research interests cover a wide range of areas including mobile and edge computing, mobile communication networks, and IoT security. He published more than 200 peer-reviewed papers including prestigious IEEE journals and conferences. He received IEEE ComSoc Best YP (Young Professional) Award in Academia in 2020, IEEE VTS Early Career Award in 2019, and the Best Paper Awards from international conferences including IEEE flagship events, such as IEEE ICC in 2023, IEEE GLOBECOM in 2019, 2022, 2024 and 2025. He is a Distinguished Lecturer of IEEE Communications Society, and a Distinguished Speaker of IEEE Vehicular Technology Society. He is a Fellow of IEEE.

Speech Title: Mobile Communication Network Security

Prof. Xiaolong Li

Hunan University of Technology and Business

Speech Title: Modeling Technologies for Cognitive Transportation Digital Twin Systems and City-Scale Application Practices

Abstract: Urban transportation digital twins are evolving from data mirroring and simulation toward cognition-driven understanding and decision support. This keynote presents recent advances in cognitive transportation digital twin modeling, focusing on unified semantic cognition, cross-regional collaborative modeling, and closed-loop adaptive optimization. It discusses how multimodal traffic data can be transformed into interpretable semantic representations of traffic objects, states, relations, constraints, and events, enabling coordinated city-scale traffic management. The talk also highlights application practices in congestion mitigation, regional coordination, and emergency response, showing how cognitive digital twins can support more resilient, adaptive, and intelligent urban mobility governance.