Chenxi LIU
Research Fellow
Computer, Electrical and Mathematical Sciences and Engineering
King Abdullah University of Science and Technology
Building 1, Room 4411, 4700 KAUST, 23955 Thuwal, Saudi Arabia

Email: chenxi.liu@kaust.edu.sa; cxliu@hnu.edu.cn

[Google Scholar] [ORCID] [GitHub]

About me | News | Publications | Awards

About Me

My name is Chenxi Liu. I am currently a Postdoctoral Research Fellow at King Abdullah University of Science and Technology (KAUST), where I have the great honor of being supervised by Prof. Panos Kalnis. Before that, I was a Research Fellow at Nanyang Technological University (NTU), working with Prof. Cheng Long and collaborating closely with Prof. Ziyue Li from the Technical University of Munich. I obtained my PhD at Hunan University, under the supervision of Prof. Dong Wang and Prof. Zhu Xiao. I also gained valuable research experience at Zhejiang Lab, supervised by Prof. Hongyang Chen.

My main research interests lie in

I will join the CAIR, Hong Kong Institute of Science & Innovation, Chinese Academy of Sciences, as an Assistant Professor. I am recruiting Research Assistants, PhD students (joint with Technical University of Munich), and Postdoctoral Research Fellows. If you are interested, please feel free to contact me via e-mail or WeChat .

News
  • 2025.11: Our GeoCRS paper is accepted by AAAI 2026 for Oral Presentation.
  • 2025.11: I will serve as a PhD mentor at the CIKM 2025 PhD Symposium. See you there and at our STIntelligence Workshop in Seoul!
  • 2025.10: Our paper is accepted by TDSC.
  • 2025.09: Join KAUST as a Postdoctoral Research Fellow!
  • 2025.08: We will organize a tutorial LLMs Meet Cross-Modal Time Series Analytics: Overview and Directions at SSTD 2025, Osaka, Japan.
  • 2025.07: We will organize the International Workshop on Spatio-Temporal Data Intelligence and Foundation Models at CIKM 2025, Seoul, Korea.
  • 2025.06: Received IJCAI-25 Travel Grant. See you all in Guangzhou!
  • 2025.05: Invited to give a talk regarding LLMs for cross-modal time series analytics at the University of New South Wales, Sydney.

Tutorial
  • [SSTD 2025] Chenxi Liu, Hao Miao, Cheng Long, Yan Zhao, Ziyue Li, Panos Kalnis: LLMs Meet Cross-Modal Time Series Analytics: Overview and Directions. 19th International Symposium on Spatial and Temporal Data, 2025. Website

Publications
  • [AAAI 2026] Yeming Li*, Chenxi Liu*, Jie Zou, Cheng Long, Chaoning Zhang, Peng Wang, Yang Yang: From Dialogue to Destination: Geography-Aware Large Language Models with Multimodal Fusion for Conversational Recommendation. Annual AAAI Conference on Artificial Intelligence, 2026. [Oral]
  • [TKDE 2026] Hao Miao, Ziqiao Liu, Yan Zhao, Chenxi Liu*, Chenjuan Guo, Bin Yang, Kai Zheng, Huan Li, Christian S. Jensen: LightTR+: A Lightweight Incremental Framework for Federated Trajectory Recovery. IEEE Transactions on Knowledge and Data Engineering, 2026.
  • [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: 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. [IF: 28]
  • [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.
  • [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.
  • [TDSC 2025] Yupeng Hu, Huiling Chen, Hongrui Pan, Wenqiang Jin, Zhenyu Ye, Chenxi Liu, Kaiyi Wang: Sound Eavesdropping on Mobile Device via Audio-Induced EMR. IEEE Transactions on Dependable and Secure Computing, 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
  • 2025, WiEST Development Grant. Women in Engineering, Science, and Technology, NTU.
  • 2025, IJCAI-25 Travel Grant, International Joint Conferences on Artificial Intelligence.
  • 2025, KDD Commendable Reviewer Recognition, Applied Data Science (ADS) Track.
  • 2024, SoBigData Award for Diversity and Inclusion, European Union.
  • 2024, DDSA Visit Grant, Danish Data Science Academy.
  • 2021, China National Computer Congress (CNCC) Travel Grant, Rank A, China Computer Federation.
  • 2017, National Scholarship, Ministry of Education.

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 CRUISE.

Services

  • PC Member: ICLR'26, WWW'26, SIGKDD'26, SIGKDD'25, ECAI'25, NeurIPS'25, WWW'25, ICML'25, IJCAI'25, ICLR'25, NeurIPS'24, MM'24, IJCAI'24, PAKDD'23.

  • Organizer: CIKM'25 STIntelligence (Publicity Chair), EAI ICECI'22 (PhD Track Chair), ICCBDAI'20 (Workshop Chair).

  • Session Chair: IJCAI'25 DM: Anomaly/outlier detection.

  • PhD Mentor: CIKM'25 PhD Symposium.

  • Reviewer: Nature Communications.

Visitors