Xiaoxia Wang | Transportation Engineering | Best Researcher Award

Published on by Academic Awards

Assoc. Prof. Dr. Xiaoxia Wang | Transportation Engineering | Best Researcher Award

Guangdong Universityof Technology | China

Assoc. Prof. Dr. Xiaoxia Wang from Guangdong University of Technology, Guangzhou, China, is a leading researcher specializing in transportation engineering, urban mobility optimization, and sustainable infrastructure. Her work bridges intelligent transportation systems, tunnel lighting design, multimodal transport behavior, and environmental assessment using advanced data-driven and machine learning models. She has authored 46 scientific publications with over 280 citations and an h-index of 9, contributing to high-impact journals such as Cities, Energy and Buildings, Tunnelling and Underground Space Technology, and Journal of Cleaner Production. Assoc. Prof. Dr. Xiaoxia Wang has successfully led several national and enterprise-funded projects focusing on energy-efficient tunnel systems, intelligent driving technologies, low-emission zone control, and urban renewal optimization.

Profile: Scopus

Featured Publications

  • Wang, X., He, Q., Cao, P., Wu, M., Jiang, Y., Zhou, H., & Yang, B. (2026). Restoring lighting quality in highway tunnels during luminaire malfunction conditions: An optimization-based luminous flux redistribution strategy. Tunnelling and Underground Space Technology, 168, 107161.

  • Tang, T., Jia, M., Zhang, Y., Hu, H., Pei, M., Chen, Y., & Wang, X. (2025). Why metro passengers change travel behavior: Individual-level insights from interpretable machine learning.

  • Wang, X., Zhou, H., Wen, R., Chen, J., He, Q., & Jiang, Y. (2025). Research on energy-saving effects of highway tunnel shading canopies based on a multi-factor control model: Revealing the influence mechanism of external luminance and optimization pathways for light environment regulation. Energy and Buildings, 116266.

  • Wang, X., Fan, Z., Yue, X., Zhou, Q., Lin, D., & Zou, H. (2025). The impact of weather on shared bikes. Applied Sciences

Zhiwei Meng | Autonomous Driving | Best Researcher Award

Published on by Academic Awards

Dr. Zhiwei Meng | Autonomous Driving | Best Researcher Award

Jilin University | China

Dr. Zhiwei Meng is an accomplished researcher whose work focuses on autonomous driving, vehicle trajectory prediction, and artificial intelligence applications in intelligent transportation systems. His research integrates advanced deep learning frameworks, attention mechanisms, and generative adversarial networks (GANs) to enhance the precision and safety of autonomous vehicle navigation. Dr. Zhiwei Meng has authored and co-authored several SCI-indexed publications in high-impact journals such as Expert Systems with Applications, IEEE Transactions on Vehicular Technology, and the Proceedings of the Institution of Mechanical Engineers, Part D: Journal of Automobile Engineering. His notable contributions, including the VectorNet-Interaction-GAN and Hierarchical Mamba frameworks, demonstrate innovation in predictive modeling and motion analysis. With 14 research papers, 39 citations, and an h-index of 4, Dr. Zhiwei Meng has established himself as a promising scholar in the field of intelligent mobility and computational vehicle dynamics, consistently contributing to advancements in data-driven decision-making for autonomous systems.

Profile: Scopus | Orcid

Featured Publications

He, R., Meng, Z., Jia, R., Cui, S., Zhang, S., & Chang, Y. (2025). HMambaOcc: Hierarchical Mamba for occupancy flow field prediction in autonomous driving under mixed traffic environments. Expert Systems with Applications, 130056.

He, R., Chang, Y., Zhang, S., Meng, Z., & Li, W. (2025). Personalized car-following strategy based on convolutional variational autoencoder and mildly conservative Q-learning. IEEE Transactions on Vehicular Technology, 3559314.

He, R., Meng, Z., Zhang, S., Cui, S., Chang, Y., Jin, X., Bai, R., & Xu, T. (2025). The SGC-Informer-based deep learning framework: Managing the efficiency–accuracy trade-off in vehicle trajectory prediction. IEEE Transactions on Vehicular Technology, 3561946.

Meng, Z., He, R., Wu, J., Zhang, S., Bai, R., & Zhi, Y. (2025). GIVA: Interaction-aware trajectory prediction based on GRU-improved VGG-attention mechanism model for autonomous vehicles. Proceedings of the Institution of Mechanical Engineers, Part D: Journal of Automobile Engineering.

He, R., Chang, Y., Zhang, S., Meng, Z., Jin, X., Bai, R., & Li, K. (2025). Microscopic traffic flow modeling method based on driving style. Proceedings of the Institution of Mechanical Engineers, Part D: Journal of Automobile Engineering.