Assistant Researcher | Zhejiang Lab | China
Dr. Xiangfu Kong is a distinguished researcher at Zhejiang Lab, specializing in intelligent transportation systems (ITS), spatiotemporal data analytics, and urban mobility optimization. His work bridges computer science, artificial intelligence, and transportation engineering to develop data-driven models that enhance mobility efficiency safety, and sustainability in smart cities.With an Publications 6 h-index of 3, and 67 citations across recognized publications, Dr. Kong has made notable scholarly contributions to the field. He has published six peer-reviewed research articles, including influential works such as “Measuring Traffic Congestion with Taxi GPS Data and Travel Time Index and A Scenario-Based Map-Matching Algorithm for Complex Urban Road Networks. His recent studies explore flood risk mapping, travel time reliability, and natural language processing for urban data interpretation, showcasing his interdisciplinary expertise.Dr. Kong’s research projects often involve large-scale real-world data, particularly GPS-based urban mobility and hydrological data, integrating AI algorithms and Bayesian frameworks to model and predict transportation dynamics under diverse conditions. His studies have direct implications for urban policy-making, disaster management, and infrastructure resilience.He has actively collaborated with industry and academic partners to design computational models that assist in traffic monitoring, path planning, and flood management, contributing to sustainable urban development initiatives. Dr. Kong’s innovative use of AI for understanding urban systems highlights his dedication to applying research outcomes to societal benefit.In addition to his publications, Dr. Kong contributes to the broader scientific community through editorial and peer-review roles in transportation and data science journals. His ongoing work in data-driven transportation intelligence and urban informatics positions him as a promising researcher contributing to the next generation of smart mobility systems.Through his research excellence and cross-disciplinary collaborations, Dr. Xiangfu Kong continues to push the boundaries of how AI and data analytics can transform urban transportation, improve public safety, and drive global sustainability efforts.
Featured Publications
1. Kong, X., Yang, J., & Yang, Z. (2015). Measuring traffic congestion with taxi GPS data and travel time index. Proceedings of the CICTP 2015, 3751–3762. Cited By : 35
2. Kong, X., & Yang, J. (2019). A scenario-based map-matching algorithm for complex urban road network. Journal of Intelligent Transportation Systems, 23(6), 617–631.
Cited By : 19
3. Kong, X., Yang, J., Qiu, J., Zhang, Q., Chen, X., Wang, M., & Jiang, S. (2022). Post‐event flood mapping for road networks using taxi GPS data. Journal of Flood Risk Management, Cited By : 8
4. Xiangfu, K., Bo, D., Xu, K., & Yongliang, T. (2023). Text classification model for livelihood issues based on BERT: A study based on hotline compliant data of Zhejiang province. Acta Scientiarum Naturalium Universitatis Pekinensis, 59(3), 456–466. Cited By : 3
5. Kong, X., & Yang, J. (2016). Path planning with information on travel time reliability. Proceedings of the CICTP 2016, 99–107. Cited By : 2
6. Kong, X., Yang, J., Xu, K., Dong, B., & Jiang, S. (2023). A Bayesian updating framework for calibrating hydrological parameters of road network using taxi GPS data. Hydrology and Earth System Sciences Discussions, 1–25.
Dr. Xiangfu Kong nresearch advances data-driven intelligent transportation and urban informatics, fostering safer, more efficient, and sustainable mobility systems. His innovative integration of AI, GPS analytics, and hydrological modeling contributes to scientific progress, climate-resilient infrastructure, and smart city innovation with lasting global impact.