Chenxi Liu
Research Fellow
S-LAB, Nanyang Technological University
ABN-02b-11, Academic Block North, 61 Nanyang Dr, Singapore

Email: chenxi.liu@ntu.edu.sg; cxliu@hnu.edu.cn

[Google Scholar] [ResearchGate] [ORCID] [GitHub]

About me | Publications | Awards | Book | Services

About Me

I am currently a research fellow at S-Lab, Nanyang Technological University (NTU), where I am supervised by Prof. Cheng Long and collaborate closely with Prof. Ziyue Li from the University of Cologne. Previously, I pursued my PhD in the College of Computer Science and Electronic Engineering, Hunan University (HNU), advised by Prof. Dong Wang and Prof. Zhu Xiao. I also gained research experience as an intern at Zhejiang Lab, supervised by Prof. Hongyang Chen.

My research interests primarily focus on time series analytics, spatio-temporal data mining, trajectory computing, large language models, and multimodal learning.

Publications
  • [TKDE 2025] Chenxi Liu, Kethmi Hirushini Hettige, Qianxiong Xu, Cheng Long, Shili Xiang, Gao Cong, Ziyue Li, Rui Zhao: ST-LLM+: Graph Enhanced Spatio-Temporal Large Language Models for Traffic Prediction. IEEE Transactions on Knowledge and Data Engineering, 2025.
  • [IJCAI 2025] Chenxi Liu, Shaowen Zhou, Qianxiong Xu, Hao Miao, Cheng Long, Ziyue Li, Rui Zhao: Towards Cross-Modality Modeling for Time Series Analytics: A Survey in the LLM Era. International Joint Conference on Artificial Intelligence, 2025.
  • [ICDE 2025] Chenxi Liu, Hao Miao, Qianxiong Xu, Shaowen Zhou, Cheng Long, Yan Zhao, Ziyue Li, Rui Zhao: Efficient Multivariate Time Series Forecasting via Calibrated Language Models with Privileged Knowledge Distillation. IEEE International Conference on Data Engineering, 2025.
  • [AAAI 2025] Chenxi Liu, Qianxiong Xu, Hao Miao, Sun Yang, Lingzheng Zhang, Cheng Long, Ziyue Li, Rui Zhao: TimeCMA: Towards LLM-Empowered Multivariate Time Series Forecasting via Cross-Modality Alignment. Annual AAAI Conference on Artificial Intelligence, 2025. [Oral Presentation: Top 4.6%]
  • [CSUR 2025] Chenxi Liu, Zhu Xiao, Wangchen Long, Tong Li, Hongbo Jiang, Keqin Li: Vehicle Trajectory Processing, Analytics, and Applications: A Survey. ACM Computing Surveys, 2025. [Impact Factor: 23.8]
  • [T-ITS 2025] Chenxi Liu, Zhu Xiao, Cheng Long, Dong Wang, Tao Li, Hongbo Jiang: MVCAR: Multi-View Collaborative Graph Network for Private Car Carbon Emission Prediction. IEEE Transactions on Intelligent Transportation Systems, 2025.
  • [MDM 2024] Chenxi Liu, Sun Yang, Qianxiong Xu, Zhishuai Li, Cheng Long, Ziyue Li, Rui Zhao: Spatial-Temporal Large Language Model for Traffic Prediction. IEEE International Conference on Mobile Data Management, 2024. 🏆 [Top-1 Most Cited Paper among Accepted Papers]
  • [ICDE 2024] Ziqiao Liu, Hao Miao, Yan Zhao, Chenxi Liu, Kai Zheng, Huan Li: LightTR: A Lightweight Framework for Federated Trajectory Recovery. IEEE International Conference on Data Engineering, 2024.
  • [DESA 2024] Sun Yang, Qiong Su, Zhishuai Li, Ziyue Li, Hangyu Mao, Chenxi Liu, Rui Zhao: SQL-to-Schema Enhances Schema Linking in Text-to-SQL. International Conference on Database and Expert Systems Applications, 2024.
  • [WWWJ 2024] Jiawei Cai, Dong Wang, Hongyang Chen, Chenxi Liu, Zhu Xiao: Modeling Dynamic Spatiotemporal User Preference for Location Prediction: A Mutually Enhanced Method. World Wide Web, 2024.
  • [WWWJ 2023] Chenxi Liu, Zhu Xiao, Dong Wang, Minhao Cheng, Hongyang Chen, Jiawei Cai: Foreseeing Private Car Transfer between Urban Regions with Multiple Graph-based Generative Adversarial Networks. World Wide Web, 2023.
  • [TNSE 2022] Chenxi Liu, Zhu Xiao, Dong Wang, Lei Wang, Hongbo Jiang, Jiangxia Yu: Exploiting Spatiotemporal Correlations of Arrive-Stay-Leave Behaviors for Private Car Flow Prediction. IEEE Transactions on Network Science and Engineering, 2022.
  • [JSEN 2021] Chenxi Liu, Jiawei Cai, Dong Wang, Jiaxin Tang, Lei Wang, Huiling Chen, Zhu Xiao: Understanding the Regular Travel Behavior of Private Vehicles: An Empirical Evaluation and A Semi-supervised Model. IEEE Sensors Journal, 2021.
  • [T-ITS 2021] Jianhua Xiao, Zhu Xiao, Dong Wang, Vincent Havyarimana, Chenxi Liu, Chengming Zhou, Di Wu: Vehicle Trajectory Interpolation Based on Ensemble Transfer Regression. IEEE Transactions on Intelligent Transportation Systems, 2021.
  • [JOC 2021] Chenxi Liu, Dong Wang, Huiling Chen, Renfa Li: Forecasting Urban Private Car Volumes based on Multi-source Heterogeneous Data Fusion. Journal on Communication, 2021.
  • [ISCI 2021] Guangyin Jin, Chenxi Liu, Zhexu Xi, Hengyu Sha, Yanyun Liu, Jincai Huang: Adaptive Dual-View WaveNet for Urban Spatial-temporal Event Prediction. Information Sciences, 2021.
  • [HPCC 2020] Huiling Chen, Dong Wang, Chenxi Liu: Towards Semantic Travel Behavior Prediction for Private Car Users. IEEE International Conference on High Performance Computing and Communications, 2020.

Awards

Book
  • 2022, Practical Applications of Deep Learning in Traffic Big Data, Tsinghua University Press (ISBN: 978-7-302-60292-7)
    • Authored Chapter 9, which provides an exploration of practical approaches to private vehicle trajectory data mining.

Talk
  • May 2025, Large Language Models Meet Cross-Modal Time Series Analytics at CRUIS.

Services

Visitors