My study aims to develop interactive, trustworthy intelligent systems comprised of autonomous agents, capable of understanding and making rational decisions in the physical environment. These agents are designed to ensure safe interaction and cooperation with other agents, road infrastructures, and humans, while effectively coordinating with intelligent agents and systems.
To achieve this, I utilize digital twin technology to create virtual models of real-world systems, enabling real-time monitoring, optimization, and simulation. Furthermore, generative AI enhances these systems by facilitating the simulation of scenarios and agent behaviors, enabling the prediction of complex interactions and adaptation to dynamic uncertainties. This development lay a strong foundation for safer, more efficient transportation systems that positively impact daily human activities.
To realize this ambition, I am dedicating myself to interdisciplinary research, integrating insights and methodologies from diverse fields such as transportation engineering, machine learning, computational optimization, generative AI, and digital twin technologies.
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University of Wisconsin-MadisonPh.D. in Civil and Environmental EngineeringSep. 2019 - Jun. 2024M.S. in Computer SciencesJan. 2020 - May 2022 -
Carnegie Mellon UniversityM.S. in Civil and Environmental EngineeringSep. 2017 - Dec. 2018 -
Southeast UniversityB.E. in Civil EngineeringSep. 2013 - Jul. 2017
Experience
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Texas A&M UniversityPostdoctoral Research AssociateAug. 2024 - Present -
University of Wisconsin-MadisonResearch AssistantSep. 2019 - Jun. 2024
News
Selected Publications (view all )
A Deep Learning Enabled Economical Informatization Framework with Sparsely Located Sensors
Wu, K., Zhou, Y., Li, X., Ye, X., Tu, Z.
Under Review 2025
A Deep Learning Enabled Economical Informatization Framework with Sparsely Located Sensors
Wu, K., Zhou, Y., Li, X., Ye, X., Tu, Z.
Under Review 2025
V2XSynth: An LLM-Driven, Retrieval-Augmented Framework for Realistic V2X Scenario Synthesis
Wu, K., Zhang, H., Li, P., Gan, R., You, J., Tu, Z., Zhou, Y.
Under Review 2025
V2XSynth: An LLM-Driven, Retrieval-Augmented Framework for Realistic V2X Scenario Synthesis
Wu, K., Zhang, H., Li, P., Gan, R., You, J., Tu, Z., Zhou, Y.
Under Review 2025
AI²-Active Safety: AI-enabled Interaction-aware Active Safety Analysis with Vehicle Dynamics
Wu, K., Li, Z., Li, S., Ye, X., Lord, D., Zhou, Y.
Under Review 2025
AI²-Active Safety: AI-enabled Interaction-aware Active Safety Analysis with Vehicle Dynamics
Wu, K., Li, Z., Li, S., Ye, X., Lord, D., Zhou, Y.
Under Review 2025
Hypergraph-based Motion Generation with Multi-modal Interaction Relational Reasoning
Wu, K., Zhou, Y., Shi, H., Lord, D., Ran, B., Ye, X.
Transportation Research Part C: Emerging Technologies 2025
Hypergraph-based Motion Generation with Multi-modal Interaction Relational Reasoning
Wu, K., Zhou, Y., Shi, H., Lord, D., Ran, B., Ye, X.
Transportation Research Part C: Emerging Technologies 2025
V2X-LLM: Enhancing V2X Integration and Understanding in Connected Vehicle Corridors
Wu, K., Li, P., Zhou, Y., Gan, R., You, J., Cheng, Y., Zhu, J., Parker, S. T., Noyce, D., Ran, B., Tu, Z.
Under Review 2025
V2X-LLM: Enhancing V2X Integration and Understanding in Connected Vehicle Corridors
Wu, K., Li, P., Zhou, Y., Gan, R., You, J., Cheng, Y., Zhu, J., Parker, S. T., Noyce, D., Ran, B., Tu, Z.
Under Review 2025
A Digital Twin Framework for Physical-Virtual Integration in Enhancing Connected Vehicle Corridor Data Pipeline
Wu, K., Li, P., Cheng, Y., Parker, S. T., Noyce, D.,, Ran, B., Ye, X.
IEEE Transactions on Intelligent Transportation Systems 2025
A Digital Twin Framework for Physical-Virtual Integration in Enhancing Connected Vehicle Corridor Data Pipeline
Wu, K., Li, P., Cheng, Y., Parker, S. T., Noyce, D.,, Ran, B., Ye, X.
IEEE Transactions on Intelligent Transportation Systems 2025
Graph-Based Interaction-Aware Multimodal 2D Vehicle Trajectory Prediction Using Diffusion Graph Convolutional Networks
Wu, K., Zhou, Y., Shi, H., Li, X., Ran, B.
IEEE Transactions on Intelligent Vehicles 2024
Graph-Based Interaction-Aware Multimodal 2D Vehicle Trajectory Prediction Using Diffusion Graph Convolutional Networks
Wu, K., Zhou, Y., Shi, H., Li, X., Ran, B.
IEEE Transactions on Intelligent Vehicles 2024