Greetings! I am Keshu Wu, a researcher working at the intersection of artificial intelligence, cyber-physical systems, and intelligent transportation. My research focuses on developing interactive and trustworthy intelligent systems that perceive, reason, and make decisions in complex physical environments. These systems aim to enable safe and coordinated interactions among humans, infrastructure, and autonomous agents, supporting the next generation of intelligent mobility and infrastructure systems.
My research specifically involves:
2) Digital Twin and Cyber-Physical Systems — building end-to-end digital twin pipelines that integrate data, simulation, and system optimization, while leveraging generative AI and LLM-based reasoning to synthesize scenarios and agent behaviors.
3) Spatiotemporal AI for Networked Systems — developing methods for spatiotemporal reconstruction, forecasting, and scalable spatial–temporal network analysis to enable data fusion and system understanding across large-scale dynamic networks.
My theoretical foundation draws on machine learning, generative AI, network science, and computational optimization, integrated with transportation engineering and cyber-physical systems, with the goal of improving transportation safety, efficiency, and everyday human mobility.
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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