Members
Lab Director
Yuxuan Liang
Assistant Professor, HKUST(GZ)
Dr. Yuxuan Liang is working on the research, development, and innovation of spatio-temporal data mining and AI, with a broad range of applications in smart cities. He obtained his PhD degree from School of Computing, National University of Singapore. He had three-year industrial experience in Microsoft, JD.COM, and Sea AI Lab. He has published 100+ papers in refereed journals (e.g., TPAMI, AI, TKDE, TNNLS, TMC) and conferences (e.g., KDD, NeurIPS, ICML, ICLR, WWW). These publications have gathered 6,700+ citations on Google Scholar, with an h-index of 42. Among them, three papers were selected as the most influential IJCAI/KDD papers via PaperDigest.
He has served as the Associate Editor of Neurocomputing (IF=6.0), the Area Chair for prestigious conferences such as KDD, MM, and ICASSP, and the Senior PC Member for IJCAI. He has also served as the organizer or co-chair of the Workshop on Urban Computing (Urbcomp@KDD), the Workshop on AI for Time Series (AI4TS@IJCAI/AAAI), and the Workshop on Mining and Learning from Time Series (MiLeTS@KDD).
He was recognized as Stanford/Elsevier Top 2% Scientists in 2024. He received ACM SIGSPATIAL China Rising Star Nomination Award in 2024, The 23rd China Patent Excellence Award in 2021, and SDSC Dissertation Research Fellowship in 2020.
PhD Students
Xixuan Hao
From HKU
2023-Present: Multimodal Learning, Spatio-Temporal Data Mining
Weichuang Li
From CityU
2023-Present: Generative Models, Implicit Neural Representation
Wei Chen
From OUC
2023-Present: Data Mining, Causal Discovery, Information Retrieval
Xusen Guo
From SYSU
2023-Present: Intelligent Transportation, Urban Computing, LLM, Agent
Jiaxi Hu
From CityU
2024-Present: Time Series, Natural Language Architecture, Multimodal
Qiongyan Wang
From UCPH
2024-Present: Spatio-Temporal Data Mining, Multimodal Learning
Siru Zhong
From HKUST(GZ)
2025-Present: Spatio-Temporal Data Mining, Multimodal Learning
Mphil Students
Yuehong Hu
From CSU
2023-Present: Data Mining, Time Series, Recommender system
Xingchen Zou
From HKU
2023-Present: Data Mining, AI for Geotechnical Engineering
Jianxiang Zhou
From SUSTech
2023-Present: Spatio-Temporal Data Mining, Graph Neural Network
Erdong Liu
From SCUT
2023-Present: Spatio-Temporal Data Mining, Urban Computing, Time Series
Yanchen Zhu
From SCUT
2023-Present: Data mining, Reinforcement learning, Heuristic algorithm
Sicong Lai
From GZHU
2023-Present: Data Mining, Urban Computing, Graph learning
Gefeng Luo
From Tongji University
2023-Present: Urban Computing, Data Minining
Xin Zuo
From ECNU
2023-Present: Spatio-Temporal Reinforcement Learning
Yuqian Wang
From CHU
2023-Present: Dispatching Algorithms, Ride-sourcing Service
Yutong Feng
From SCUT
2023-Present: Spatio-Temporal Data Mining, Federate Learning
Weilin Ruan
From JNU
2024-Present: Spatio-Temporal Data Mining, Multimodal Learning
Yongzheng Liu
From ZJU
2024-Present: Spatio-Temporal Data Mining, Multimodal, Smart Energy
Ziyu Zhou
From BJUT
2024-Present: Time series, Machine Learning
Songxin Lei
From Tianjin University
2024-Present: Urban Sensing, Reinforcement learning, Multimodal
Huang Lan
From SCAU
2024-Present: Spatio-Temporal Data Mining, Multimodal
Sisuo LYU
From HIT(SZ)
2024-Present: Time series, Spatio-Temporal Data Mining
Research Assistant
Yutian Jiang
From JLU
2024-Present: Multimodal, Artificial Intelligence
Research Interns
Yuanshao Zhu
From SUSTech
2023-Present: Spatio-Temporal Data Mining, Trajectory Analysis
Jiabo Liu
From JNU
2024-Present: Spatio-Temporal Data Mining, Multimodal
Junjie Qiu
From SUSTech
2024-Present: Trajectory Data Mining, Robotics
Yongqi Pan
From NUDT
2024-Present: Model lightweight, Object tracking, Blockchain
Zepu Wang
From UW
2024-Present: Spatio-Temporal Data Mining, Time Series, Transportation
Qingxiang Liu
From CAS
2023-Present: Time Series Analysis, Federated Learning
Alumni
Research Intern
- Qingren Yao (2024) Master student, Tianjin University -> PhD Student, Griffith University.
- Bowen Zhang (2024) Undergraduate student, South China University of Technology -> PhD student, Chinese University of Hong Kong.
- Disen Lan (2023～2024) Undergraduate student, South China University of Technology-> PhD student, Fudan University & Shanghai AI Lab.
- Haomin Wen (2023~2024) PhD student, Beijing Jiaotong University -> Postdoc, Carnegie Mellon University.
- Kun Wang (2023) PhD student, University of Science and Technology of China -> Postdoc, Nanyang University of Technology.
- Guibing Zhang (2023～2024) Undergraduate student, Tongji University.
- Lilan Peng (2023～2024) PhD student, Southwest Jiaotong University.
- Kang Luo (2023～2024) Master student, Zhejiang University.
- Haodong Chen (2023～2024) Undergraduate student, Northwestern Polytechnical University.
- Wentao Zeng (2023) Undergraduate student, Northeastern University.
Research Assistant
- Qingren Yao (2024~2025) Master student, Tianjin University -> PhD student, Griffith University
- Jie Zhao (2024) PhD student, Chongqing University -> Postdoc, Tsinghua University.
- Huaiwu Zhang (2023～2024) Master student, University of Chinese Academy of Sciences -> PhD student, University of Helsinki.
- Yibo Yan (2023～2024) Master student, National University of Singapore -> PhD student, Hong Kong University of Science and Technology (Guangzhou).
Outside HKUST(GZ)
Our team is also very lucky to collaborate with the following talented students (in alphabetical order):
- Haomin Wen (PhD student, Beijing Jiaotong University), co-supervised with Prof. Youfang Lin, 2022-Present.
- Junfeng Hu (PhD student, National University of Singapore), co-supervised with Prof. Roger Zimmermann, 2021-Present.
- Kun Wang (PhD student, University of Science and Technology of China), co-supervised with Prof. Yang Wang, 2022-Present.
- Xu Liu (PhD student, National University of Singapore), co-supervised with Prof. Roger Zimmermann, 2021-Present.
- Yoojin An (Master, Dongguk University), co-supervised with Prof. Jihie Kim, 2021-2022.
- Yutong Xia (PhD student, National University of Singapore), co-supervised with Prof. Roger Zimmermann, 2022-Present.
Collaborators
We are honored to closely work with the following researchers:
