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, supervised by Prof. Roger Zimmermann and Prof. David S. Rosenblum. He had three years of industrial experience in Microsoft, JD Technology, and Sea AI Lab, working closely with Dr. Yu Zheng and Dr. Junbo Zhang.

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 ~7,000 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 was recognized as Stanford/Elsevier Top 2% Scientists in 2024, and 1 out of 10 most innovative and impactful PhD students focusing on Data Science in Singapore by Singapore Data Science Consortium (SDSC) in 2020. He also received ACM SIGSPATIAL China Rising Star Nomination Award in 2024, and The 23rd China Patent Excellence Award in 2021.

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 has organized a series of tutorials on spatio-temporal data mining and time series analysis at prestigious conferences, such as KDD, WWW, AAAI, IJCAI, MM, and MDM.

His research interests mainly lie in:

  • Spatio-temporal (ST) data mining: ST foundation models, Urban/ST + LLMs, AI for social good (e.g., urban, transportation, human mobility, environment, climate), physics-informed learning.
  • Urban computing: urban data sensing, urban data management, urban data analytics, urban decision-making.
  • Time series analysis: foundation models, forecasting, imputation, decomposition, anomaly detection.
  • Multimodal learning: multimodal fusion, vision-language models.

PhD Students

Xixuan Hao
M.S from The University of Hong Kong
2023-Present: Multimodal Learning, Spatio-Temporal Data Mining

Weichuang Li
M.S from City University of Hong Kong
2023-Present: Generative Models, Implicit Neural Representation

Wei Chen
M.S from Ocean University of China
2023-Present: Data Mining, Causal Discovery, Information Retrieval

Xusen Guo
M.S from Sun Yat-sen University
2023-Present: Intelligent Transportation, Urban Computing, LLM, Agent

Jiaxi Hu
M.S from City University of Hong Kong
2024-Present: Time Series, Natural Language Architecture, Multimodal

Qiongyan Wang
M.S from University of Copenhagen
2024-Present: Spatio-Temporal Data Mining, Multimodal Learning

Siru Zhong
M.S from Hong Kong University of Science and Technology (GZ)
2025-Present: Spatio-Temporal Data Mining, Time Series, Multimodal

Xingchen Zou
M.S from Hong Kong University of Science and Technology (GZ)
2025-Present: Data Mining, AI for Geotechnical Engineering

Yangyu Wu
M.S from Capital Normal University
2025-Present: LLM for Spatio-Temporal Learning, Natural Language Processing

Yutian Jiang
B.S from Jilin University
2025-Present: Computer Vision, Representation Learning, Vision Language Model

Mphil Students

Yuehong Hu
B.S from Central South University
2023-Present: Data Mining, Time Series, Recommender system

Jianxiang Zhou
B.S from Southern University of Science and Technology
2023-Present: Spatio-Temporal Data Mining, Graph Neural Network

Yanchen Zhu
B.S from South China University of Technology
2023-Present: Data mining, Reinforcement learning, Heuristic algorithm

Erdong Liu
B.S from South China University of Technology
2023-Present: Spatio-Temporal Data Mining, Urban Computing, Time Series

Sicong Lai
B.S from Guangzhou University
2023-Present: Data Mining, Urban Computing, Graph learning

Yutong Feng
B.S from South China University of Technology
2023-Present: Spatio-Temporal Data Mining, Federate Learning

Gefeng Luo
B.S from Tongji University
2023-Present: Urban Computing, Data Minining

Xin Zuo
B.S from East China Normal University
2023-Present: Spatio-Temporal Reinforcement Learning

Yuqian Wang
B.S from Chang’an University
2023-Present: Dispatching Algorithms, Ride-sourcing Service

Weilin Ruan
B.S from Jinan University
2024-Present: Spatio-Temporal Data Mining, Multimodal Learning

Yongzheng Liu
B.S from Zhejiang University
2024-Present: Spatio-Temporal Data Mining, Multimodal, Smart Energy

Ziyu Zhou
B.S from Beijing University of Technology
2024-Present: Time series, Machine Learning

Songxin Lei
B.S from Tianjin University
2024-Present: Urban Sensing, Reinforcement learning, Multimodal

Huang Lan
B.S from South China Agricultural University
2024-Present: Spatio-Temporal Data Mining, Multimodal

Sisuo LYU
B.S from Harbin Institute of Technology (SZ)
2024-Present: Time series, Spatio-Temporal Data Mining

Jiabo Liu
B.S from Jinan University
2025-Present: Spatio-Temporal Data Mining, Multimodal

Research Assistant

Junjie Qiu
B.S from Southern University of Science and Technology
2024-Present: Trajectory Data Mining, Robotics

Research Interns

Yongqi Pan
Ph.D. student from  National University of Defense Technology
2024-Present: Model lightweight, Object tracking, Blockchain

Zepu Wang
Ph.D. student from University of Washington
2024-Present: Spatio-Temporal Data Mining, Time Series, Transportation

Qingxiang Liu
Ph.D. student from Chinese Academy of Sciences
2023-Present: Time Series Analysis, Federated Learning

Alumni

Research Intern

  • Yuanshao Zhu (2023~2025) PhD student, Southern University of Science and Technology & City University of Hong Kong
  • 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 -> PhD student, National University of Singapore.
  • 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: