Publications

2026

1. 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},
   }

2025

1. 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},
   }

2. NeurIPS

   

   TimeEmb: A Lightweight Static-Dynamic Disentanglement Framework for Time Series Forecasting

   Mingyuan Xia, Chunxu Zhang, Zijian Zhang, Hao Miao, Qidong Liu, Yuanshao Zhu , and Bin Yang

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

   Bib PDF Code

   @inproceedings{xia2025timeemb,
     title = {TimeEmb: A Lightweight Static-Dynamic Disentanglement Framework for Time Series Forecasting},
     author = {Xia, Mingyuan and Zhang, Chunxu and Zhang, Zijian and Miao, Hao and Liu, Qidong and Zhu, Yuanshao and Yang, Bin},
     booktitle = {Proceedings of the 39th Annual Conference on Neural Information Processing Systems},
     year = {2025},
   }

3. KDD

   Building a Global-Scale Trajectory Dataset from OpenStreetMap

   Yuanshao Zhu

   In KDD 2025 PhD Consortium Program, 2025

   Bib PDF

   @inproceedings{zhu2025phd,
     title = {Building a Global-Scale Trajectory Dataset from OpenStreetMap},
     author = {Zhu, Yuanshao},
     booktitle = {KDD 2025 PhD Consortium Program},
     year = {2025},
   }

4. 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},
   }

5. arXiv

   

   Select, then Balance: A Plug-and-Play Framework for Exogenous-Aware Spatio-Temporal Forecasting

   Wei Chen, Yuqian Wu, Yuanshao Zhu , Xixuan Hao, Shiyu Wang, and Yuxuan Liang

   arXiv preprint arXiv:2509.05779, 2025

   Bib PDF

   @article{chen2025select,
     title = {Select, then Balance: A Plug-and-Play Framework for Exogenous-Aware Spatio-Temporal Forecasting},
     author = {Chen, Wei and Wu, Yuqian and Zhu, Yuanshao and Hao, Xixuan and Wang, Shiyu and Liang, Yuxuan},
     journal = {arXiv preprint arXiv:2509.05779},
     year = {2025},
   }

6. AAAI

   

   LLMEmb: Large Language Model Can Be a Good Embedding Generator for Sequential Recommendation

   Qidong Liu, Xian Wu, Wanyu Wang, Yejing Wang, Yuanshao Zhu , Xiangyu Zhao, Feng Tian, and Yefeng Zheng

   In Proceedings of the AAAI Conference on Artificial Intelligence, 2025

   Bib PDF Blog Code

   @inproceedings{liu2025llmemb,
     title = {LLMEmb: Large Language Model Can Be a Good Embedding Generator for Sequential Recommendation},
     author = {Liu, Qidong and Wu, Xian and Wang, Wanyu and Wang, Yejing and Zhu, Yuanshao and Zhao, Xiangyu and Tian, Feng and Zheng, Yefeng},
     booktitle = {Proceedings of the AAAI Conference on Artificial Intelligence},
     year = {2025},
   }

7. AAAI

   

   POI-Enhancer: An LLM-based Semantic Enhancement Framework for POI Representation Learning

   Jiawei Cheng, Jingyuan Wang, Yichuan Zhang, Jiahao Ji, Yuanshao Zhu , Zhibo Zhang, and Xiangyu Zhao

   In Proceedings of the AAAI Conference on Artificial Intelligence, 2025

   Bib PDF Blog Code

   @inproceedings{cheng2025poi,
     title = {POI-Enhancer: An LLM-based Semantic Enhancement Framework for POI Representation Learning},
     author = {Cheng, Jiawei and Wang, Jingyuan and Zhang, Yichuan and Ji, Jiahao and Zhu, Yuanshao and Zhang, Zhibo and Zhao, Xiangyu},
     booktitle = {Proceedings of the AAAI Conference on Artificial Intelligence},
     year = {2025},
   }

8. AAAI

   

   UniTR: A Unified Framework for Joint Representation Learning of Trajectories and Road Networks

   Jie Zhao, Chao Chen, Yuanshao Zhu , Mingyu Deng, and Yuxuan Liang

   In Proceedings of the AAAI Conference on Artificial Intelligence, 2025

   Bib PDF Code

   @inproceedings{zhao2025unitr,
     title = {UniTR: A Unified Framework for Joint Representation Learning of Trajectories and Road Networks},
     author = {Zhao, Jie and Chen, Chao and Zhu, Yuanshao and Deng, Mingyu and Liang, Yuxuan},
     booktitle = {Proceedings of the AAAI Conference on Artificial Intelligence},
     year = {2025},
   }

9. AAAI

   

   GARLIC: GPT-Augmented Reinforcement Learning with Intelligent Control for Vehicle Dispatching

   Xiao Han, Zijian Zhang, Xiangyu Zhao, Yuanshao Zhu , Guojiang Shen, Xiangjie Kong, Xuetao Wei, Liqiang Nie, and Jieping Ye

   In Proceedings of the AAAI Conference on Artificial Intelligence, 2025

   Bib PDF Blog

   @inproceedings{han2025garlic,
     title = {GARLIC: GPT-Augmented Reinforcement Learning with Intelligent Control for Vehicle Dispatching},
     author = {Han, Xiao and Zhang, Zijian and Zhao, Xiangyu and Zhu, Yuanshao and Shen, Guojiang and Kong, Xiangjie and Wei, Xuetao and Nie, Liqiang and Ye, Jieping},
     booktitle = {Proceedings of the AAAI Conference on Artificial Intelligence},
     year = {2025},
   }

2024

1. 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},
   }

2. SIGIR

   

   When MOE Meets LLMs: Parameter Efficient Fine-tuning for Multi-task Medical Applications

   Qidong Liu, Xian Wu, Xiangyu Zhao, Yuanshao Zhu , Derong Xu, Feng Tian, and Yefeng Zheng

   In Proceedings of the 47th International ACM SIGIR Conference on Research and Development in Information Retrieval, 2024

   Bib PDF Blog Code

   @inproceedings{liu2024moelora,
     title = {When MOE Meets LLMs: Parameter Efficient Fine-tuning for Multi-task Medical Applications},
     author = {Liu, Qidong and Wu, Xian and Zhao, Xiangyu and Zhu, Yuanshao and Xu, Derong and Tian, Feng and Zheng, Yefeng},
     booktitle = {Proceedings of the 47th International ACM SIGIR Conference on Research and Development in Information Retrieval},
     year = {2024},
     pages = {1104–1114},
     numpages = {11},
   }

3. arXiv

   Large Language Model Distilling Medication Recommendation Model

   Qidong Liu, Xian Wu, Xiangyu Zhao, Yuanshao Zhu , Zijian Zhang, Feng Tian, and Yefeng Zheng

   arXiv preprint arXiv:2402.02803, 2024

   Bib PDF Code

   @article{liu2024llmdist,
     title = {Large Language Model Distilling Medication Recommendation Model},
     author = {Liu, Qidong and Wu, Xian and Zhao, Xiangyu and Zhu, Yuanshao and Zhang, Zijian and Tian, Feng and Zheng, Yefeng},
     journal = {arXiv preprint arXiv:2402.02803},
     year = {2024},
   }

4. IJCAI

   Towards Robust Trajectory Representations: Isolating Environmental Confounders with Causal Learning

   Kang Luo, Yuanshao Zhu , Wei Cheng, Kun Wang, Zhengyang Zhou, Sijie Ruan, and Yuxuan Liang

   In Proceedings of the 33rd international joint conference on artificial intelligence, 2024

   Bib PDF

   @inproceedings{Luo2024TrajCL,
     title = {Towards Robust Trajectory Representations: Isolating Environmental Confounders with Causal Learning},
     author = {Luo, Kang and Zhu, Yuanshao and Cheng, Wei and Wang, Kun and Zhou, Zhengyang and Ruan, Sijie and Liang, Yuxuan},
     booktitle = {Proceedings of the 33rd international joint conference on artificial intelligence},
     year = {2024},
   }

5. arXiv

   Deep Learning for Trajectory Data Management and Mining: A Survey and Beyond

   Wei Chen, Yuxuan Liang, Yuanshao Zhu , Yanchuan Chang, Kang Luo, Haomin Wen, Lei Li, Yanwei Yu, Qingsong Wen, and 5 more authors

   arXiv preprint arXiv:2403.14151, 2024

   Bib PDF Blog Code

   @article{chen2024deep,
     title = {Deep Learning for Trajectory Data Management and Mining: A Survey and Beyond},
     author = {Chen, Wei and Liang, Yuxuan and Zhu, Yuanshao and Chang, Yanchuan and Luo, Kang and Wen, Haomin and Li, Lei and Yu, Yanwei and Wen, Qingsong and Chen, Chao and Zheng, Kai and Gao, Yunjun and Zhou, Xiaofang and Zheng, Yu},
     journal = {arXiv preprint arXiv:2403.14151},
     year = {2024},
   }

2023

1. 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},
   }

2. 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},
   }

3. ITSC

   Data-Driven Methods for Travel Time Estimation: A Survey

   Zhipeng Zheng, Yongchao Ye, Yuanshao Zhu , Shiyao Zhang, and James J.Q. Yu

   In 2023 IEEE 26th International Conference on Intelligent Transportation Systems (ITSC), 2023

   Bib PDF

   @inproceedings{ETASurvey,
     author = {Zheng, Zhipeng and Ye, Yongchao and Zhu, Yuanshao and Zhang, Shiyao and Yu, James J.Q.},
     booktitle = {2023 IEEE 26th International Conference on Intelligent Transportation Systems (ITSC)},
     title = {Data-Driven Methods for Travel Time Estimation: A Survey},
     year = {2023},
     volume = {},
     number = {},
     pages = {1292-1299},
   }

4. WWW

   AutoDenoise: Automatic Data Instance Denoising for Recommendations

   Weilin Lin, Xiangyu Zhao, Yejing Wang, Yuanshao Zhu , and Wanyu Wang

   In ACM Web Conference 2023 (WWW), 2023

   Bib PDF

   @inproceedings{AutoDenoise,
     title = {AutoDenoise: Automatic Data Instance Denoising for Recommendations},
     author = {Lin, Weilin and Zhao, Xiangyu and Wang, Yejing and Zhu, Yuanshao and Wang, Wanyu},
     booktitle = {ACM Web Conference 2023 (WWW)},
     year = {2023},
   }

5. TITS

   Traffic Prediction With Transfer Learning: A Mutual Information-Based Approach

   Yunjie Huang, Xiaozhuang Song, Yuanshao Zhu , Shiyao Zhang, and James J.Q. Yu

   IEEE Transactions on Intelligent Transportation Systems, 2023

   Bib PDF

   @article{huang2023traffic,
     author = {Huang, Yunjie and Song, Xiaozhuang and Zhu, Yuanshao and Zhang, Shiyao and Yu, James J.Q.},
     journal = {IEEE Transactions on Intelligent Transportation Systems},
     title = {Traffic Prediction With Transfer Learning: A Mutual Information-Based Approach},
     year = {2023},
   }

6. arXiv

   Enhancing Traffic Prediction with Learnable Filter Module

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

   arXiv preprint arXiv:2310.16063, 2023

   Bib PDF

   @article{zhu2023filter,
     title = {Enhancing Traffic Prediction with Learnable Filter Module},
     author = {Zhu, Yuanshao and Ye, Yongchao and Zhao, Xiangyu and Yu, James J.Q.},
     journal = {arXiv preprint arXiv:2310.16063},
     year = {2023},
   }

2022

1. TITS

   CatETA: A Categorical Approximate Approach for Estimating Time of Arrival

   Yongchao Ye^’, Yuanshao Zhu^’ , Christos Markos, and James J.Q. Yu

   IEEE Transactions on Intelligent Transportation Systems, 2022

   Bib PDF

   @article{CatETA,
     author = {Ye', Yongchao and Zhu', Yuanshao and Markos, Christos and Yu, James J.Q.},
     journal = { IEEE Transactions on Intelligent Transportation Systems},
     title = {CatETA: A Categorical Approximate Approach for Estimating Time of Arrival},
     year = {2022},
   }

2. 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},
   }

2021

1. ICTAI

   Improving Transportation Mode Identification with Limited GPS Trajectories

   Yuanshao Zhu , Christos Markos, and James J.Q. Yu

   In 2021 IEEE 33rd International Conference on Tools with Artificial Intelligence (ICTAI), 2021

   Bib PDF

   @inproceedings{zhuIctai,
     author = {Zhu, Yuanshao and Markos, Christos and Yu, James J.Q.},
     booktitle = {2021 IEEE 33rd International Conference on Tools with Artificial Intelligence (ICTAI)},
     title = {Improving Transportation Mode Identification with Limited GPS Trajectories},
     year = {2021},
     pages = {655-660},
   }

2. IJCNN

   FedOVA: One-vs-All Training Method for Federated Learning with Non-IID Data

   Yuanshao Zhu , Christos Markos, Ruihui Zhao, Yefeng Zheng, and James J.Q. Yu

   In 2021 International Joint Conference on Neural Networks (IJCNN), 2021

   Bib PDF

   @inproceedings{Zhufedova,
     author = {Zhu, Yuanshao and Markos, Christos and Zhao, Ruihui and Zheng, Yefeng and Yu, James J.Q.},
     booktitle = {2021 International Joint Conference on Neural Networks (IJCNN)},
     title = {FedOVA: One-vs-All Training Method for Federated Learning with Non-IID Data},
     year = {2021},
   }

3. TNSE

   Resource-constrained Federated Learning with Heterogeneous Data: Formulation and Analysis

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

   IEEE Transactions on Network Science and Engineering, 2021

   Bib PDF

   @article{zhuTnse,
     author = {Liu, Yi and Zhu, Yuanshao and Yu, James J.Q.},
     journal = {IEEE Transactions on Network Science and Engineering},
     title = {Resource-constrained Federated Learning with Heterogeneous Data: Formulation and Analysis},
     year = {2021},
     equal = {true},
   }

4. IoTJ

   Toward Crowdsourced Transportation Mode Identification: A Semisupervised Federated Learning Approach

   Chaoyun Zhang, Yuanshao Zhu , Christos Markos, Shui Yu, and James J.Q. Yu

   IEEE Internet of Things Journal, 2021

   Bib

   @article{zhang2021crowdsourced,
     author = {Zhang, Chaoyun and Zhu, Yuanshao and Markos, Christos and Yu, Shui and Yu, James J.Q.},
     journal = {IEEE Internet of Things Journal},
     title = {Toward Crowdsourced Transportation Mode Identification: A Semisupervised Federated Learning Approach},
     year = {2021},
   }

5. 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},
   }

2020

1. ICPADS

   Robust Federated Learning Approach for Travel Mode Identification from Non-IID GPS Trajectories

   Yuanshao Zhu , Shuyu Zhang, Yi Liu, Dusit Niyato, and James J.Q. Yu

   In 2020 IEEE 26th International Conference on Parallel and Distributed Systems (ICPADS), 2020

   Bib PDF

   @inproceedings{zhu2020robust,
     title = {Robust Federated Learning Approach for Travel Mode Identification from Non-IID GPS Trajectories},
     author = {Zhu, Yuanshao and Zhang, Shuyu and Liu, Yi and Niyato, Dusit and Yu, James J.Q.},
     booktitle = {2020 IEEE 26th International Conference on Parallel and Distributed Systems (ICPADS)},
     year = {2020},
   }