I am currently a postdoctoral fellow at Data Intelligence Lab@HKU collaborating with Professor Chao Huang. I also work with Professor Ben Kao. My research works lie in data science, with a focus on applications ranging from Information Retrieval, Robust and Efficient Graph Mining, User Behavior Modeling, AI for Urban Science, and Trustworthy AI. I received my Ph.D. and Bachelor degrees in computer science at South China University of Technology (SCUT) adviced by Professor Yong Xu.

Research Interests

• Data Mining, AI-Generated Content for Graph;
• Graph Learning, Self-Supervised Learning;
• User Behavior Modeling, Recommendation;
• Spatio-Temporal Mining, AI for Urban Science.

Highlights

• [06/2023] - Recognized as AI 2000 Most Influential Scholars (2022-2023) by Aminer in Data Mining (Ranked 15th) and Information Retrieval (Ranked 19th)
• [06/2023] - We release the first programming library on Self-Supervised Learning for Recommendation
• [05/2023] - My first-authored paper AutoCF is selected as Spotlight Paper & Best Paper Nomination of WWW'2023 (Top 4.4%)
• [05/2023] - My first-authored paper MB-GMN is featured in the Top-10 Most-Cited Paper of SIGIR'2021 (Top 6.6%)
• [04/2023] - My first-authored paper HCCF and co-authored paper KGCL are featured in Most Influential Papers of SIGIR'2022 (Ranked 2nd and 3rd)
• [04/2023] - My co-authored paper LightGCL is selected as Spotlight Paper of ICLR'2023 (Top 25%)
• [10/2022] - I participate in a tutorial on Self-Supervised Learning for Recommendation at CIKM'2022
• [02/2022] - My co-authored paper CML is selected as Best Paper Candidate of WSDM'2022
• [12/2021] - I received He-Jingtang Innovation Prize (only 2 winners throughout university)
• [09/2021] - National Scholarship and Presidential Scholarship for Ph.D. Candidates

Selected Publications

I have published 13 first-authored papers in top-tier publication venues in different fields such as Information Retrieval (SIGIR, WWW, TOIS), Data Mining (KDD, WSDM, TKDE), Artificial Intelligence (ICLR, ICML, AAAI, IJCAI, TNNLS), and Database (ICDE). My publications gained some highly selective awards, including Two Most Influential Papers (ranked 2nd & 3rd), Two Spotlight Papers (acceptance rate 4.4% & 25%), Two Most Cited Papers (ranked 2nd & 10th), and Best Paper Candidate. For a full list of my publications: Full List of Lianghao's Publications.

• [NeurIPS'24] "GPT-ST: Generative Pre-Training of Spatio-Temporal Graph Neural Networks"
  Advances in Neural Information Processing Systems
  Z. Li, L. Xia, Y. Xu and C. Huang
  [pdf] [code]

• [WWW'24] "GraphPro: Graph Pre-training and Prompt Learning for Recommendation"
  ACM The Web Conference
  Y. Yang, L. Xia, D. Luo, K. Lin and C. Huang
  [pdf] [code]

• [WSDM'24] "SSLRec: A Self-Supervised Learning Framework for Recommendation"
  ACM International Conference on Recommender Systems
  X. Ren, L. Xia, Y. Yang, W. Wei, T. Wang, X. Cai and C. Huang
  [pdf] [code]

• [WWW'24] "RLMRec: Representation Learning with Large Language Models for Recommendation"
  ACM The Web Conference
  X. Ren, W. Wei, L. Xia, L. Su, S. Cheng, J. Wang, D. Yin and C. Huang
  [pdf] [code]

• [WWW'23] "Automated Self-Supervised Learning for Recommendation"
  ACM The Web Conference
  Spotlight Paper & Best Paper Nominations (Acceptance Rate 16 / 365 = 4.4%)
  L. Xia, C. Huang, C.Z. Huang, K. Lin, T. Yu and B. Kao
  [pdf] [code]

• [WWW'23] "Graph-less Collaborative Filtering"
  ACM The Web Conference
  L. Xia, C. Huang, J. Shi and Y. Xu
  [pdf] [code]

• [ICDE'23] "Disentangled Graph Social Recommendation"
  IEEE International Conference on Data Engineering
  L. Xia, Y. Shao, C. Huang, Y. Xu, H. Xu and J. Pei
  [pdf] [code]

• [WWW'23] "Debiased Contrastive Learning for Sequential Recommendation"
  ACM The Web Conference
  Y. Yang, C. Huang, L. Xia, C.Z. Huang, D. Luo and K. Lin
  Top-5 Most-Cited Paper in WWW'23 (Acceptance Rate 5 / 323 = 1.5%)
  [pdf] [code]

• [WWW'23] "Multi-Modal Self-Supervised Learning for Recommendation"
  ACM The Web Conference
  W. Wei, C. Huang, L. Xia and C. Zhang
  Featured in Most Influential Paper in WWW'23 (Ranked 3rd)
  [pdf] [code]

• [ICLR'23] "LightGCL: Simple Yet Effective Graph Contrastive Learning for Recommendation"
  International Conference on Learning Representations
  Selected as Spotlight Paper (Top 25%)
  X. Cai, C. Huang, L. Xia and X. Ren
  [pdf] [code]

• [WSDM'23] "Heterogeneous Graph Contrastive Learning for Recommendation"
  ACM International Conference on Web Search and Data Mining
  M. Chen, C. Huang, L. Xia, W. Wei, Y. Xu and R. Luo
  Top-3 Most-Cited Paper in WSDM'23 (Acceptance Rate 3 / 123 = 2.4%)
  [pdf] [code]

• [ICML'23] "Spatial-Temporal Graph Learning with Adversarial Contrastive Adaptation"
  International Conference on Machine Learning
  Q. Zhang, C. Huang, L. Xia, Z. Wang, S.M. Yiu and R. Han
  [pdf] [code]

• [SIGIR'22] "Hypergraph Contrastive Collaborative Filtering"
  International ACM SIGIR Conference on Research and Development in Information Retrieval
  Featured in Most Influential Papers in SIGIR'22 (Ranked 2nd)
  L. Xia, C. Huang, Y. Xu, J. Zhao, D. Yin and J. Huang
  [pdf] [code]

• [KDD'22] "Self-Supervised Hypergraph Transformer for Recommender Systems"
  ACM SIGKDD Conference on Knowledge Discovery and Data Mining
  L. Xia, C. Huang and C. Zhang
  [pdf] [code]

• [TNNLS'22] "Multi-Behavior Graph Neural Networks for Recommender System"
  IEEE Transactions on Neural Networks and Learning Systems
  L. Xia, C. Huang, Y. Xu, P. Dai and L. Bo
  [pdf] [code]

• [TKDE'22] "Multi-Behavior Sequential Recommendation with Temporal Graph Transformer"
  IEEE Transactions on Data Engineering
  L. Xia, C. Huang, Y. Xu and J. Pei
  [pdf] [code]

• [SIGIR'22] "Knowledge Graph Contrastive Learning for Recommendation"
  International ACM SIGIR Conference on Research and Development in Information Retrieval
  Featured in Most Influential Papers in SIGIR'22 (Ranked 3rd)
  Y. Yang, C. Huang, L. Xia and C. Li
  [pdf] [code]

• [WSDM'22] "Contrastive Meta Learning with Behavior Multiplicity for Recommendation"
  ACM International Conference on Web Search and Data Mining
  Best Paper Candidate & Top-2 Most Cited Paper among All 159 Papers
  W. Wei, C. Huang, L. Xia, Y. Xu, J. Zhao, D. Yin
  [pdf] [code]

• [SIGIR'21] "Graph Meta Network for Multi-Behavior Recommendation"
  International ACM SIGIR Conference on Research and Development in Information Retrieval
  Top-10 Most Cited Papers in SIGIR'21 (Acceptance Rate 10 / 152 = 6.6%)
  L. Xia, Y. Xu, C. Huang, P. Dai and L. Bo
  [pdf] [code]

• [AAAI'21] "Knowledge-Enhanced Hierarchical Graph Transformer Network for Multi-Behavior Recommendation"
  AAAI Conference on Artificial Intelligence
  L. Xia, C. Huang, Y. Xu, P. Dai, M. Lu and L. Bo
  [pdf] [code]

• [TOIS'21] "Collaborative Reflection-Augmented Autoencoder Network for Recommender Systems"
  ACM Transactions on Information Systems
  L. Xia, C. Huang, Y. Xu, H. Xu, X. Li and W. Zhang
  [pdf] [code]

• [ICDE'21] "Multi-Behavior Enhanced Recommendation with Cross-Interaction Collaborative Relation Modeling"
  IEEE International Conference on Data Engineering
  L. Xia, C. Huang, Y. Xu, P. Dai, M. Lu and L. Bo
  [pdf] [code]

• [SIGIR'20] "Multiplex Behavioral Relation Learning for Recommendation via Memory Augmented Transformer Network"
  International ACM SIGIR Conference on Research and Development in Information Retrieval
  L. Xia, C. Huang, Y. Xu, P. Dai and L. Bo
  [pdf] [code]

Education Background

• South China University of Technology

  09/2017-12/2021
  Ph.D., at Department of Computer Science and Technology
• South China University of Technology

  09/2013-06/2017
  Bachelor, Majored in Computer Science and Technology (English-Taught Class)

Work Experience

• The University of Hong Kong

  06/2022-Present
  Postdoctoral Fellow, at Department of Computer Science and Institute of Data Science
• Microsoft Research Asia

  09/2016-05/2017
  Research Software Development Intern, at Innovation Engineering Group

Services

Program Commitee Member of Conferences:

• In year 2024: SIGIR, KDD, WWW, AAAI, ICLR, SDM
• In year 2023: SIGIR, KDD, WWW, AAAI, NeurIPS
• In year 2022: KDD, AAAI

Reviewer for Journals:

• IEEE Transactions: TKDE, TBD, TNNLS, TLT
• ACM Transactions: TOIS, TWEB, TKDD
• APIN, DMKD, Neural Networks, Information Science

Presentations

• 05/2023  Spotlight Paper presentation at WWW'2023
• 05/2023  Talk at Hunan University
• 12/2022  Talk at Institute of Computing Technology, Chinese Academy of Sciences
• 10/2022  Tutorial on Self-Supervised Learning for Recommendation at CIKM'2022
• 12/2021  Talk at Guangdong University of Technology
• 11/2021  Talk at College of Future Technology, SCUT
• Research paper presentations at international conferences:
  SIGIR'2023, WWW'2023, ICDE'2023, SIGIR'2022, SIGIR'2021, ICDE'2021, SIGIR'2020