Yuanshao Zhu

Ph.D. Candidate, CityU
Hong Kong, China
yaso.zhu@my.cityu.edu.hk
Google Scholar GitHub DBLP

I’m a Ph.D. student in CityU(SDS) under the supervision of Prof. James Jianqiao Yu, Prof. Xiangyu Zhao, and Prof. Xuetao Wei. Previously, I received my B.S. degree from Shandong University in 2019 and M.S. degree from Southern University of Science and Technology in 2022.

My research interests lie at the intersection of artificial intelligence, smart cities, and data mining, with a focus on trajectory representation, generation, and prediction in urban mobility scenarios. I develop foundation models for trajectory data, explore diffusion-based generative methods for controllable trajectory synthesis, and apply Large Language Models to human mobility analysis.

Selected publications

AAAI

Boosting Fine-Grained Urban Flow Inference via Lightweight Architecture and Focalized Optimization

Yuanshao Zhu , Xiangyu Zhao, Zijian Zhang, Xuetao Wei, and James Jianqiao Yu

In Proceedings of the AAAI conference on artificial intelligence, 2026

Bib PDF Blog Code

@inproceedings{zhu2026boosting,
  title = {Boosting Fine-Grained Urban Flow Inference via Lightweight Architecture and Focalized Optimization},
  author = {Zhu, Yuanshao and Zhao, Xiangyu and Zhang, Zijian and Wei, Xuetao and Yu, James Jianqiao},
  booktitle = {Proceedings of the AAAI conference on artificial intelligence},
  volume = {40},
  year = {2026},
}

NeurIPS

UniTraj: Learning a Universal Trajectory Foundation Model from Billion-Scale Worldwide Traces

Yuanshao Zhu , James Jianqiao Yu, Xiangyu Zhao, Xun Zhou, Liang Han, Xuetao Wei, and Yuxuan Liang

In Proceedings of the 39th Annual Conference on Neural Information Processing Systems, 2025

Bib PDF Blog Code

@inproceedings{zhu2025unitraj,
  title = {UniTraj: Learning a Universal Trajectory Foundation Model from Billion-Scale Worldwide Traces},
  author = {Zhu, Yuanshao and Yu, James Jianqiao and Zhao, Xiangyu and Zhou, Xun and Han, Liang and Wei, Xuetao and Liang, Yuxuan},
  booktitle = {Proceedings of the 39th Annual Conference on Neural Information Processing Systems},
  year = {2025},
}

KDD

Learning Generalized and Flexible Trajectory Models from Omni-Semantic Supervision

Yuanshao Zhu , James Jianqiao Yu, Xiangyu Zhao, Xiao Han, Qidong Liu, Xuetao Wei, and Yuxuan Liang

In Proceedings of the 31st ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2025

Bib PDF Code

@inproceedings{zhu2025learning,
  title = {Learning Generalized and Flexible Trajectory Models from Omni-Semantic Supervision},
  author = {Zhu, Yuanshao and Yu, James Jianqiao and Zhao, Xiangyu and Han, Xiao and Liu, Qidong and Wei, Xuetao and Liang, Yuxuan},
  booktitle = {Proceedings of the 31st ACM SIGKDD Conference on Knowledge Discovery and Data Mining},
  year = {2025},
}

KDD

ControlTraj: Controllable Trajectory Generation with Topology-Constrained Diffusion Model

Yuanshao Zhu , James Jianqiao Yu, Xiangyu Zhao, Qidong Liu, Yongchao Ye, Wei Chen, Zijian Zhang, Xuetao Wei, and Yuxuan Liang

In Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2024

Bib PDF Blog Code

@inproceedings{zhu2024controltraj,
  title = {ControlTraj: Controllable Trajectory Generation with Topology-Constrained Diffusion Model},
  author = {Zhu, Yuanshao and Yu, James Jianqiao and Zhao, Xiangyu and Liu, Qidong and Ye, Yongchao and Chen, Wei and Zhang, Zijian and Wei, Xuetao and Liang, Yuxuan},
  booktitle = {Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining},
  year = {2024},
}

NeurIPS

DiffTraj: Generating GPS Trajectory with Diffusion Probabilistic Model

Yuanshao Zhu , Yongchao Ye, Shiyao Zhang, Xiangyu Zhao, and James J.Q. Yu

In Proceedings of the 37th Annual Conference on Neural Information Processing Systems, 2023

Bib PDF Blog Code

@inproceedings{zhu2023difftraj,
  title = {DiffTraj: Generating GPS Trajectory with Diffusion Probabilistic Model},
  author = {Zhu, Yuanshao and Ye, Yongchao and Zhang, Shiyao and Zhao, Xiangyu and Yu, James J.Q.},
  booktitle = {Proceedings of the 37th Annual Conference on Neural Information Processing Systems},
  year = {2023},
}

NeurIPS

SynMob: Creating High-Fidelity Synthetic GPS Trajectory Dataset for Urban Mobility Analysis

Yuanshao Zhu^’ , Yongchao Ye^’, Ying Wu, Xiangyu Zhao, and James J.Q. Yu

In Proceedings of the 37th Annual Conference on Neural Information Processing Systems, 2023

Bib PDF Blog Code

@inproceedings{zhu2023synmob,
  title = {SynMob: Creating High-Fidelity Synthetic GPS Trajectory Dataset for Urban Mobility Analysis},
  author = {Zhu', Yuanshao and Ye', Yongchao and Wu, Ying and Zhao, Xiangyu and Yu, James J.Q.},
  booktitle = {Proceedings of the 37th Annual Conference on Neural Information Processing Systems},
  year = {2023},
}

TITS

Cross-Area Travel Time Uncertainty Estimation From Trajectory Data: A Federated Learning Approach

Yuanshao Zhu^’ , Yongchao Ye^’, Yi Liu, and James J.Q. Yu

IEEE Transactions on Intelligent Transportation Systems, 2022

Bib PDF

@article{FedETA,
  author = {Zhu', Yuanshao and Ye', Yongchao and Liu, Yi and Yu, James J.Q.},
  journal = {IEEE Transactions on Intelligent Transportation Systems},
  title = {Cross-Area Travel Time Uncertainty Estimation From Trajectory Data: A Federated Learning Approach},
  year = {2022},
}

TITS

Semi-Supervised Federated Learning for Travel Mode Identification From GPS Trajectories

Yuanshao Zhu , Yi Liu, James J.Q. Yu, and Xingliang Yuan

IEEE Transactions on Intelligent Transportation Systems, 2021

Bib PDF

@article{zhusemi,
  author = {Zhu, Yuanshao and Liu, Yi and Yu, James J.Q. and Yuan, Xingliang},
  journal = {IEEE Transactions on Intelligent Transportation Systems},
  title = {Semi-Supervised Federated Learning for Travel Mode Identification From {GPS} Trajectories},
  year = {2021},
  pages = {1-12},
}