Ziyue Li

Assistant Professor

University of Cologne

Germany

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Dr. Ziyue Li is an Assistant Professor at Universität zu Köln, Germany. His research areas include traffic prediction using large language models, reinforcement learning for traffic signal control, and noise-robust trajectory recovery frameworks. Recent publications illustrate his focus on innovative approaches in spatio-temporal data analysis and decision-making for multi-agent systems.

Articles (17)

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2025

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2020

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2020

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2020

Collaborators (4)

Hao Yan

Assistant Professor

Arizona State University

UNITED STATES

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Stefano Canali

Junior Assistant Professor (RTD-A)

Politecnico di Milano

ITALY

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Philip Yu

Distinguished Professor & Wexler Chair in Information Technology

University of Chicago

UNITED STATES

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Cheng Long

Assistant Professor

Nanyang Technological University (NTU)

SINGAPORE

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Ziyue Li

Research Interests

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Articles (17)

ST-LLM+: Graph Enhanced Spatio-Temporal Large Language Models for Traffic Prediction

Online Test-Time Adaptation of Spatial–Temporal Traffic Flow Forecasting

VisionTraj: A Noise-Robust Trajectory Recovery Framework Based on Large-Scale Camera Network

FELight: Fairness-Aware Traffic Signal Control via Sample-Efficient Reinforcement Learning

DTPPO: Dual-Transformer Encoder-Based Proximal Policy Optimization for Multi-UAV Navigation in Unseen Complex Environments

Controlling Large Language Model-based Agents for Large-Scale Decision-Making: An Actor-Critic Approach

A General Scenario-Agnostic Reinforcement Learning for Traffic Signal Control

Relation-Aware Distribution Representation Network for Person Clustering With Multiple Modalities

Choose A Table: Tensor Dirichlet Process Multinomial Mixture Model with Graphs for Passenger Trajectory Clustering

The paradox of the artificial intelligence system development process: the use case of corporate wellness programs using smart wearables

Individualized passenger travel pattern multi-clustering based on graph regularized tensor latent dirichlet allocation

Profile Decomposition based Hybrid Transfer Learning for Cold-start Data Anomaly Detection

Jointly Contrastive Representation Learning on Road Network and Trajectory

Tensor Completion for Weakly-Dependent Data on Graph for Metro Passenger Flow Prediction

Discussion of “A novel approach to the analysis of spatial and functional data over complex domains”

Long-Short Term Spatiotemporal Tensor Prediction for Passenger Flow Profile

Long-Short Term Spatiotemporal Tensor Prediction for Passenger Flow Profile

Collaborators (4)

Hao Yan

Stefano Canali

Philip Yu

Cheng Long

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