Dr. Wan Li has an outstanding academic background that underpins his expertise in transportation systems and data-driven solutions. He earned his Ph.D. in Civil and Environmental Engineering from the University of Washington (2016-2019), where he specialized in advanced modeling and optimization techniques for urban traffic networks. Prior to that, he completed his M.S. in Civil and Environmental Engineering at Louisiana State University (2012-2014), where he gained a solid foundation in transportation systems engineering. His academic journey began with a B.S. in Traffic Engineering from Sun Yat-sen University (2008-2012), where he developed his initial interest in mobility and traffic control. This robust educational trajectory has significantly contributed to his innovative research and professional achievements in the field of transportation engineering.
Experience
Currently, Dr. Li is a Research Associate Staff at Oak Ridge National Laboratory (2022-Present), where he leads and contributes to groundbreaking projects funded by the U.S. Department of Energy (DOE). These include initiatives like AI-based adaptive signal timing optimization for urban areas, fleet electrification, and the development of EV ecosystems in economically distressed regions. As a Lead Researcher, he has driven innovative projects such as the deployment of AI for electric motor design, the use of foundation models for time-series predictions, and optimized mobility through signal coordination and CAV integration. His previous roles include Postdoctoral Researcher at Oak Ridge National Laboratory (2019-2022), AI Engineer at Huawei, and Algorithm Engineer at DiDi, each emphasizing his expertise in data-driven traffic optimization and ML-based solutions.
Research Interests
Dr. Wan Li’s research focuses on the modeling, simulation, and optimization of urban traffic networks, including the design and optimization of traffic control systems incorporating Connected and Autonomous Vehicles (CAVs). He also specializes in transportation big data analytics using machine learning (ML) and artificial intelligence (AI) and is deeply invested in transportation energy solutions, showcasing a strong commitment to sustainable and efficient mobility systems.
Skills
Dr. Wan Li possesses a wide range of advanced skills in transportation systems, AI, and energy optimization. His expertise includes modeling, simulation, and optimization of urban traffic networks, with a focus on integrating connected and autonomous vehicles (CAVs) into traffic control systems. He is proficient in applying machine learning (ML) and artificial intelligence (AI) for transportation big data analytics, energy efficiency, and mobility optimization. Dr. Li is highly skilled in traffic signal control, with experience in AI-based adaptive signal timing and the development of innovative systems to reduce congestion and energy consumption. His work in transportation energy and sustainable mobility also extends to electric vehicle (EV) ecosystem development and green economy initiatives. Additionally, Dr. Li has strong project management skills, having led multiple high-impact research initiatives funded by the U.S. Department of Energy (DOE) and other leading organizations. His technical proficiency is complemented by a deep understanding of the interdisciplinary aspects of urban mobility, AI, and energy systems.
Publication
- Title: Cooperative method of traffic signal optimization and speed control of connected vehicles at isolated intersections
Authors: B. Xu, XJ. Ban, Y. Bian, W. Li, J. Wang, SE. Li, K. Li
Journal: IEEE Transactions on Intelligent Transportation Systems
Volume: 20, Issue: 4, Pages: 1390-1403
Cited by: 274
Year: 2018
- Title: Connected vehicles based traffic signal timing optimization
Authors: W. Li, X. Ban
Journal: IEEE Transactions on Intelligent Transportation Systems
Volume: 20, Issue: 12, Pages: 4354-4366
Cited by: 104
Year: 2019
- Title: Two-stream multi-channel convolutional neural network for multi-lane traffic speed prediction considering traffic volume impact
Authors: R. Ke, W. Li, Z. Cui, Y. Wang
Journal: Transportation Research Record
Volume: 2674, Issue: 4, Pages: 459-470
Cited by: 99
Year: 2020
- Title: Dynamic traffic signal timing optimization strategy incorporating various vehicle fuel consumption characteristics
Authors: J. Zhao, W. Li, J. Wang, X. Ban
Journal: IEEE Transactions on Vehicular Technology
Volume: 65, Issue: 6, Pages: 3874-3887
Cited by: 89
Year: 2015
- Title: Short-term traffic state prediction from latent structures: accuracy vs. efficiency
Authors: W. Li, J. Wang, R. Fan, Y. Zhang, Q. Guo, C. Siddique, XJ. Ban
Journal: Transportation Research Part C: Emerging Technologies
Volume: 111, Pages: 72-90
Cited by: 83
Year: 2020
Conclusion
Dr. Wan Li’s multidisciplinary expertise in traffic engineering, ML/AI-driven solutions, and energy-efficient transportation systems, along with his impactful research and leadership in transformative projects, make him a strong contender for the Research for Best Researcher Award. His work not only advances academic knowledge but also contributes significantly to solving real-world transportation and sustainability challenges.