Portrait of Keshu Wu

Keshu Wu

Research Associate
UW-Madison
  • Intelligent Transportation
  • Artificial Intelligence
  • Cyber-Physical Systems

About Me

Greetings! I am Keshu Wu, a Postdoctoral Researcher at University of Wisconsin–Madison, working at the intersection of intelligent transportation, artificial intelligence, and cyber-physical systems.

I received a Ph.D. degree in Civil and Environmental Engineering from the University of Wisconsin–Madison. I also hold an M.S. degree in Computer Sciences from the University of Wisconsin–Madison, and an M.S. degree in Civil and Environmental Engineering from Carnegie Mellon University. I received a B.E. degree in Civil Engineering from Southeast University.

Research Interests

01Autonomous Mobility Intelligence

Higher-order multi-agent interaction modeling and relational reasoning; Multimodal motion prediction, planning, and control; Safety-critical decision-making and mixed-traffic intelligence.

02Agentic Mobility & Foundation Models

Agentic systems and multi-agent orchestration; LLM/VLM-enabled reasoning and control; Retrieval-augmented intelligence; Generative and long-tail scenario synthesis.

03Spatiotemporal & Geospatial AI

Graph/hypergraph learning; Higher-order networks; Spatiotemporal reconstruction and forecasting; Geospatial foundation models; Multimodal sensing and data fusion.

04Digital Twins, World Models & Cyber-Physical Systems

Data-grounded and multi-fidelity digital twins; Generative world modeling; Physical–virtual closed-loop simulation; Resilience and safety-critical stress testing.

05Connected & Cooperative Mobility Systems

V2X and air–ground cooperation; Vehicle–road–edge–cloud intelligence; Connected infrastructure analytics; Distributed sensing, communication, and control.

Experience

  • Oct. 2026 - Present
    University of Wisconsin-Madison
    University of Wisconsin-Madison
    Research Associate
  • Aug. 2024 - Sept. 2026
    Texas A&M University
    Texas A&M University
    Postdoctoral Research Associate
  • Oct. 2024 - Sept. 2026
    Texas A&M Institute of Data Science (TAMIDS)
    Texas A&M Institute of Data Science (TAMIDS)
    Research Affiliate
  • Sep. 2019 - Jun. 2024
    University of Wisconsin-Madison
    University of Wisconsin-Madison
    Research Assistant

Education

  • Sep. 2019 - Jun. 2024
    University of Wisconsin-Madison
    University of Wisconsin-Madison
    Ph.D. in Civil and Environmental Engineering
    M.S. in Computer Sciences
  • Sep. 2017 - Dec. 2018
    Carnegie Mellon University
    Carnegie Mellon University
    M.S. in Civil and Environmental Engineering
  • Sep. 2013 - Jul. 2017
    Southeast University
    Southeast University
    B.E. in Civil Engineering

News

  1. 2026
  2. Sep I will give a lectern presentation at MIDTRANS 2026 in Lawrence, KS.
  3. Aug Our paper is accepted in principle by Nature Communications.
  4. Jan I will present 8 research posters at TRBAM 2026 in Washington, D.C.
  5. 2025
  6. Jan I will present 1 podium talk and 5 research posters at TRBAM 2025 in Washington, D.C.
  7. 2024
  8. Aug I will be joining CEE and LAUP at Texas A&M University as a postdoc.
  9. Jun I will present 1 podium talk at ASCE ICTD 2024 in Atlanta, GA.
  10. May I received my Ph.D. degree from the UW-Madison.
  11. 2023
  12. Jun I will present 1 podium talk at ASCE ICTD 2023 in Austin, TX.

Selected Publications

View all
LAST-V2X: Language-Driven Adaptive Scenario Synthesis and Testing for Communication-Induced Failures in V2X Safety ApplicationsUnder Review
LAST-V2X: Language-Driven Adaptive Scenario Synthesis and Testing for Communication-Induced Failures in V2X Safety Applications

Wu, K., Zhang, H., Gan, R., Li, P., Jiang, J., Zhou, Y.

Under Review (2026)

[Preprint] [Website]

# LLM# RAG# V2X# scenario generation

Under Review
LAST-V2X: Language-Driven Adaptive Scenario Synthesis and Testing for Communication-Induced Failures in V2X Safety Applications

Wu, K., Zhang, H., Gan, R., Li, P., Jiang, J., Zhou, Y.

Under Review 2026

[Preprint] [Website]

# LLM# RAG# V2X# scenario generation

A Deep Learning Enabled Economical Informatization Framework with Sparsely Located SensorsNat. Commun.
A Deep Learning Enabled Economical Informatization Framework with Sparsely Located Sensors

Wu, K., Zhou, Y., Li, X., Ye, X., Tu, Z.

Nature Communications (2026) (accepted in principle)

# inductive learning# hybrid sensor network# graph transformer

Nat. Commun.
A Deep Learning Enabled Economical Informatization Framework with Sparsely Located Sensors

Wu, K., Zhou, Y., Li, X., Ye, X., Tu, Z.

Nature Communications 2026 (accepted in principle)

# inductive learning# hybrid sensor network# graph transformer

AURORA: A Natural Language–Driven Agentic Framework for Understanding, Reasoning, and Orchestrating Reliable Air–Ground Co-SimulationUnder Review
AURORA: A Natural Language–Driven Agentic Framework for Understanding, Reasoning, and Orchestrating Reliable Air–Ground Co-Simulation

Wu, K., Zhang, H., Gan, R., Gao, X., Li, X., Tu, Z., Zhou, Y.

Under Review (2026)

[Website]

# LLM# air-ground collaboration# agentic framework# co-simulation# UAV

Under Review
AURORA: A Natural Language–Driven Agentic Framework for Understanding, Reasoning, and Orchestrating Reliable Air–Ground Co-Simulation

Wu, K., Zhang, H., Gan, R., Gao, X., Li, X., Tu, Z., Zhou, Y.

Under Review 2026

[Website]

# LLM# air-ground collaboration# agentic framework# co-simulation# UAV

Knowledge Is Not Static: Order-Aware Hypergraph RAG for Language ModelsarXiv
Knowledge Is Not Static: Order-Aware Hypergraph RAG for Language Models

Wu, K., Kuai, C., Li, Z., Jiang, J., Shen, S., Wang, S., Hu, C., Tu, Z., Zhou, Y.

Under Review (2026)

[Preprint]

# knowledge graph# hypergraph# RAG# LLM

arXiv
Knowledge Is Not Static: Order-Aware Hypergraph RAG for Language Models

Wu, K., Kuai, C., Li, Z., Jiang, J., Shen, S., Wang, S., Hu, C., Tu, Z., Zhou, Y.

Under Review 2026

[Preprint]

# knowledge graph# hypergraph# RAG# LLM

AI²-Active Safety: AI-enabled Interaction-aware Active Safety Analysis with Vehicle DynamicsarXiv
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 (2026)

[Preprint]

# active safety# vehicle dynamics# hypergraph

arXiv
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 2026

[Preprint]

# active safety# vehicle dynamics# hypergraph

Hypergraph-based Motion Generation with Multi-modal Interaction Relational ReasoningTR-C
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)

[Paper]

# hypergraph# interaction# multi-modality

TR-C
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

[Paper]

# hypergraph# interaction# multi-modality

A Digital Twin Framework for Physical-Virtual Integration in Enhancing Connected Vehicle Corridor Data PipelineIEEE T-ITS
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)

[Paper]

# digital twin# V2X# connected vehicle corridor

IEEE T-ITS
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

[Paper]

# digital twin# V2X# connected vehicle corridor

All publications