Research Overview

My research focuses on developing interactive and trustworthy intelligent systems that operate within 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:

1) Connected and Automated Mobility Intelligence: modeling interactions among vehicles, infrastructure, and humans, and developing AI methods for safe motion prediction, planning, and control within connected vehicle–road–cloud and V2X systems.
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 research integrates methods from machine learning, generative AI, network science, and computational optimization with domain knowledge in transportation engineering and cyber-physical systems. Through this interdisciplinary approach, I aim to develop intelligent infrastructure and mobility systems that improve transportation safety, efficiency, and everyday human mobility.

Overview of Keshu Wu's research: connected and automated mobility intelligence, digital twins and cyber-physical systems, and spatiotemporal AI for networked systems.

Publications

Filter by topic Showing all 21 publications

2026

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

Learning Higher-Order Structure from Incomplete Spatiotemporal Data: Multi-Scale Hypergraph Laplacians with Neural RefinementarXiv
Learning Higher-Order Structure from Incomplete Spatiotemporal Data: Multi-Scale Hypergraph Laplacians with Neural Refinement

Wu, K., Li, S., Li, Z., Fan, Z., Li, X., Zhou, Y.

Under Review (2026)

[Preprint]

# spatiotemporal imputation# hypergraph learning# higher-order structure

arXiv
Learning Higher-Order Structure from Incomplete Spatiotemporal Data: Multi-Scale Hypergraph Laplacians with Neural Refinement

Wu, K., Li, S., Li, Z., Fan, Z., Li, X., Zhou, Y.

Under Review 2026

[Preprint]

# spatiotemporal imputation# hypergraph learning# higher-order structure

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

V2XSynth: An LLM-Driven, Retrieval-Augmented Framework for Realistic V2X Scenario SynthesisUnder Review
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 (2026)

[Website]

# LLM# RAG# V2X# scenario generation

Under Review
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 2026

[Website]

# LLM# RAG# V2X# scenario generation

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

V2X-LLM: Enhancing V2X Integration and Understanding in Connected Vehicle CorridorsarXiv
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 (2026)

[Preprint]

# LLM# V2X

arXiv
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 2026

[Preprint]

# LLM# V2X

V2X-VLM: End-to-End V2X Cooperative Autonomous Driving Through Large Vision Language ModelsTR-C
V2X-VLM: End-to-End V2X Cooperative Autonomous Driving Through Large Vision Language Models

You, J., Shi, H., Jiang, Z., Huang, Z., Gan, R., Wu, K., Cheng, X., Li, X., Ran, B.

Transportation Research Part C: Emerging Technologies (2026)

[Paper]

# VLM# V2X# trajectory planning

TR-C
V2X-VLM: End-to-End V2X Cooperative Autonomous Driving Through Large Vision Language Models

You, J., Shi, H., Jiang, Z., Huang, Z., Gan, R., Wu, K., Cheng, X., Li, X., Ran, B.

Transportation Research Part C: Emerging Technologies 2026

[Paper]

# VLM# V2X# trajectory planning

2025

AirV2X: Unified Air-Ground Vehicle-to-Everything CollaborationarXiv
AirV2X: Unified Air-Ground Vehicle-to-Everything Collaboration

Gao, X., Wu, Y.,, Yang, F., Luo, X., Wu, K., Chen, X., Wang, Y., Liu, C., Zhou, Y., Tu, Z.

Under Review (2025)

[Preprint] [Website]

# cooperative perception# air-ground collaboration# V2X# UAV

arXiv
AirV2X: Unified Air-Ground Vehicle-to-Everything Collaboration

Gao, X., Wu, Y.,, Yang, F., Luo, X., Wu, K., Chen, X., Wang, Y., Liu, C., Zhou, Y., Tu, Z.

Under Review 2025

[Preprint] [Website]

# cooperative perception# air-ground collaboration# V2X# UAV

FollowGen: A Scaled Noise Conditional Diffusion Model for Car-Following Trajectory PredictionCOMMTR
FollowGen: A Scaled Noise Conditional Diffusion Model for Car-Following Trajectory Prediction

You, J., Gan, R., Tang, W., Huang, Z., Liu, J., Jiang, Z., Shi, H.,, Wu, K., Long, K., Fu, S., Chen, S., Ran, B.

Communications in Transportation Research (2025)

[Paper]

# trajectory prediction# diffusion models# car-following

COMMTR
FollowGen: A Scaled Noise Conditional Diffusion Model for Car-Following Trajectory Prediction

You, J., Gan, R., Tang, W., Huang, Z., Liu, J., Jiang, Z., Shi, H.,, Wu, K., Long, K., Fu, S., Chen, S., Ran, B.

Communications in Transportation Research 2025

[Paper]

# trajectory prediction# diffusion models# car-following

Virtual Roads, Smarter Safety: A Digital Twin Framework for Mixed Autonomous Traffic AnalysisIEEE IoT-J
Virtual Roads, Smarter Safety: A Digital Twin Framework for Mixed Autonomous Traffic Analysis

Zhang, H., Yue, X., Tian, K., Li, S., Wu, K., Li, Z.,, Lord, D., Zhou, Y.

IEEE Internet of Things Journal (2025)

[Paper]

# digital twin# active safety# autonomous vehicle# high-fidelity simulation

IEEE IoT-J
Virtual Roads, Smarter Safety: A Digital Twin Framework for Mixed Autonomous Traffic Analysis

Zhang, H., Yue, X., Tian, K., Li, S., Wu, K., Li, Z.,, Lord, D., Zhou, Y.

IEEE Internet of Things Journal 2025

[Paper]

# digital twin# active safety# autonomous vehicle# high-fidelity simulation

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 Predictive Deep Reinforcement Learning Based Connected Automated Vehicle Anticipatory Longitudinal Control in a Mixed Traffic Lane Change ConditionIEEE IoT-J
A Predictive Deep Reinforcement Learning Based Connected Automated Vehicle Anticipatory Longitudinal Control in a Mixed Traffic Lane Change Condition

Shi, H., Shi, K., Wu, K., Li, W., Zhou, Y., Ran, B.

IEEE Internet of Things Journal (2025)

[Paper]

# DRL# CAV# predictive control

IEEE IoT-J
A Predictive Deep Reinforcement Learning Based Connected Automated Vehicle Anticipatory Longitudinal Control in a Mixed Traffic Lane Change Condition

Shi, H., Shi, K., Wu, K., Li, W., Zhou, Y., Ran, B.

IEEE Internet of Things Journal 2025

[Paper]

# DRL# CAV# predictive control

Goal-based neural physics vehicle trajectory prediction modelTR-C
Goal-based neural physics vehicle trajectory prediction model

Gan, R., Shi, H., Li, P., Wu, K., An, B., Li, L., Ma, J., Ma, C., Ran, B.

Transportation Research Part C: Emerging Technologies (2025)

[Paper]

# trajectory prediction# neural differential equations# transformer

TR-C
Goal-based neural physics vehicle trajectory prediction model

Gan, R., Shi, H., Li, P., Wu, K., An, B., Li, L., Ma, J., Ma, C., Ran, B.

Transportation Research Part C: Emerging Technologies 2025

[Paper]

# trajectory prediction# neural differential equations# transformer

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

2024

How Does C-V2X Perform in Urban Environments? Results From Real-World Experiments on Urban ArterialsIEEE T-IV
How Does C-V2X Perform in Urban Environments? Results From Real-World Experiments on Urban Arterials

Li, P., Wu, K., Cheng, Y., Parker, S. T., Noyce, D. A.

IEEE Transactions on Intelligent Vehicles (2024)

[Paper]

# V2X# V2I# field experiment

IEEE T-IV
How Does C-V2X Perform in Urban Environments? Results From Real-World Experiments on Urban Arterials

Li, P., Wu, K., Cheng, Y., Parker, S. T., Noyce, D. A.

IEEE Transactions on Intelligent Vehicles 2024

[Paper]

# V2X# V2I# field experiment

Graph-Based Interaction-Aware Multimodal 2D Vehicle Trajectory Prediction Using Diffusion Graph Convolutional NetworksIEEE T-IV
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)

[Paper]

# GNN# interaction# multi-modality

IEEE T-IV
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

[Paper]

# GNN# interaction# multi-modality

2023

Physics-informed deep reinforcement learning-based integrated two-dimensional car-following control strategy for connected automated vehiclesKBS
Physics-informed deep reinforcement learning-based integrated two-dimensional car-following control strategy for connected automated vehicles

Shi, H., Zhou, Y., Wu, K., Chen, S., Ran, B., Nie, Q.

Knowledge-Based Systems (2023)

[Paper]

# DRL# CAV# 2D control

KBS
Physics-informed deep reinforcement learning-based integrated two-dimensional car-following control strategy for connected automated vehicles

Shi, H., Zhou, Y., Wu, K., Chen, S., Ran, B., Nie, Q.

Knowledge-Based Systems 2023

[Paper]

# DRL# CAV# 2D control

Development of the Data Pipeline for a Connected Vehicle CorridorASCE ICTD
Development of the Data Pipeline for a Connected Vehicle Corridor

Wu, K., Cheng, Y., Parker, S. T., Ran, B., Noyce, D. A.

ASCE International Conference on Transportation and Development 2023 (2023)

[Paper]

# data pipeline# connected vehicle# v2x corridor

ASCE ICTD
Development of the Data Pipeline for a Connected Vehicle Corridor

Wu, K., Cheng, Y., Parker, S. T., Ran, B., Noyce, D. A.

ASCE International Conference on Transportation and Development 2023 2023

[Paper]

# data pipeline# connected vehicle# v2x corridor

2022

Work zone crash occurrence prediction based on planning stage work zone configurations using an artificial neural networkTRR
Work zone crash occurrence prediction based on planning stage work zone configurations using an artificial neural network

Cheng, Y., Wu, K., Li, H., Parker, S., Ran, B., Noyce, D.

Transportation research record (2022)

[Paper]

# crash prediction# work zone

TRR
Work zone crash occurrence prediction based on planning stage work zone configurations using an artificial neural network

Cheng, Y., Wu, K., Li, H., Parker, S., Ran, B., Noyce, D.

Transportation research record 2022

[Paper]

# crash prediction# work zone

2021

Connected automated vehicle cooperative control with a deep reinforcement learning approach in a mixed traffic environmentTR-C
Connected automated vehicle cooperative control with a deep reinforcement learning approach in a mixed traffic environment

Shi, H., Zhou, Y., Wu, K., Wang, X., Lin, Y., Ran, B.

Transportation Research Part C: Emerging Technologies (2021)

[Paper]

# DRL# CAV# cooperative control

TR-C
Connected automated vehicle cooperative control with a deep reinforcement learning approach in a mixed traffic environment

Shi, H., Zhou, Y., Wu, K., Wang, X., Lin, Y., Ran, B.

Transportation Research Part C: Emerging Technologies 2021

[Paper]

# DRL# CAV# cooperative control