Maolin Wang

Maolin Wang

Ph.D. Candidate at City University of Hong Kong

Maolin Wang is a Ph.D. candidate at City University of Hong Kong, dedicated to advancing artificial intelligence efficiency and sustainability. His research focuses on natural language processing, knowledge reasoning, and generative AI, with expertise in graph learning, model compression, and tensor/matrix decomposition. Under the supervision of Prof. Xiangyu Zhao and co-supervision of Dr. Ruocheng Guo and Prof. Junhui Wang, he explores innovative approaches in model lightweight optimization and low-power consumption tuning. Prior to his doctoral studies, he received his master’s and bachelor’s degrees from the University of Electronic Science and Technology of China (UESTC) under the guidance of Prof. Zenglin Xu. His ultimate goal is to contribute to the advancement of sustainable AI that is both powerful and environmentally responsible, making AI more accessible to everyone.

🔥 News

  • 2025.02: 🎉🎉 My paper, MetaLoRA: Tensor-Enhanced Adaptive Low-Rank Fine-tuning, has been accepted by ICDE 2025 Doctoral Forum!
  • 2024.12: 🎉🎉 Our paper, GLINT-RU: Gated Lightweight Intelligent Recurrent Units for Sequential Recommender Systems, has been accepted by KDD 2025 ( I serve as co-first author) !

📝 Publications

  1. Maolin Wang. (2025). MetaLoRA: Tensor-Enhanced Adaptive Low-Rank Fine-tuning. In PhD Symposium Track at IEEE International Conference on Data Engineering (ICDE) .
  2. Sheng Zhang^, Maolin Wang^, Wanyu Wang, Jingtong Gao, Xiangyu Zhao, Yu Yang, Xuetao Wei, Zitao Liu, Tong Xu. (2025). GLINT-RU: Gated Lightweight Intelligent Recurrent Units for Sequential Recommender Systems. In SIGKDD Conference on Knowledge Discovery and Data Mining (CCF-A). (^equal contribution)
  3. Ziwei Liu, Qidong Liu, Yejing Wang, Wanyu Wang, Pengyue Jia, Maolin Wang, Zitao Liu, Yi Chang, Xiangyu Zhao. (2025). SIGMA: Selective Gated Mamba for Sequential Recommendation. In AAAI Conference on Artificial Intelligence (CCF-A).
  4. Yejing Wang, Chi Zhang, Xiangyu Zhao, Qidong Liu, Maolin Wang, Xuetao Wei, Zitao Liu, Xing Shi, Yang Xudong, Ling Zhong, Wei Lin. (2025). Behavior Modeling Space Reconstruction for E-Commerce Search. In The Web Conference (WWW) (CCF-A) [Oral].
  5. Maolin Wang, Yao Zhao, Jiajia Liu, Jingdong Chen, Chenyi Zhuang, Jinjie Gu, Ruocheng Guo, Xiangyu Zhao. (2024). Large Multimodal Model Compression via Efficient Pruning and Distillation. In The Web Conference (WWW) (CCF-A) [Oral] [Deployed in 5+ real-world scenarios at Ant Group and Alipay].
  6. Maolin Wang, Yaoming Zhen, Yu Pan, Yao Zhao, Chenyi Zhuang, Zenglin Xu, Ruocheng Guo, Xiangyu Zhao. (2024). Tensorized Hypergraph Neural Networks. In SIAM International Conference on Data Mining (SDM) (CCF-B).
  7. Sheng Zhang^, Maolin Wang^, Yao Zhao, Chenyi Zhuang, Ruocheng Guo, Xiangyu Zhao et al. (2024). DNS-Rec: Data-aware Neural Architecture Search for Recommender Systems. In ACM Conference on Recommender Systems (RecSys) (CCF-B). (^equal contribution)
  8. Maolin Wang, Dun Zeng, Zenglin Xu, Ruocheng Guo, Xiangyu Zhao. (2023). Federated Knowledge Graph Completion via Latent Embedding Sharing. In IEEE International Conference on Data Mining (ICDM) (CCF-B).
  9. Kesen Zhao, Lixin Zou, Xiangyu Zhao, Maolin Wang, Dawei Yin. (2023). User Retention-oriented Recommendation with Decision Transformer. In The Web Conference (WWW) (CCF-A).
  10. Xiaopeng LI^, Maolin Wang^, and Hing Cheung So. (2022). An Interpretable Bi-Branch Neural Network for Matrix Completion. In Signal Processing (SCI-Q2). (^equal contribution)
  11. Yu Pan, Maolin Wang, and Zenglin Xu. (2021). TedNet: A Pytorch Toolkit For Tensor Decomposition Networks. In Neurocomputing (SCI-Q2) [100+ stars in Github].
  12. Maolin Wang, Zeyong Su, Xu Luo, Yu Pan, Shenggen Zheng and Zenglin Xu. (2020). Concatenated Tensor Networks for Deep Multi-Task Learning. In International Conference on Neural Information Processing (ICONIP) (CCF-C).
  13. Maolin Wang, Chenbin Zhang, Yu Pan, Jing Xu and Zenglin Xu. (2019). Tensor Ring Restricted Boltzmann Machines. In International Joint Conference on Neural Networks (IJCNN) (CCF-C) Oral.
  14. Yu Pan, Jing Xu, Maolin Wang, Jinmian Ye, Fei Wang, Kun Bai, and Zenglin Xu. (2019). Compressing Recurrent Neural Networks with Tensor Ring for Action Recognition. In AAAI Conference on Artificial Intelligence (AAAI) (CCF-A).

📝 Patent

  1. Xiao Peng LI, Hing Cheung SO, Maolin Wang. METHOD AND ELECTRONIC DEVICE FOR RECOVERING DATA USING BI-BRANCH NEURAL NETWORK. U.S. Patent.

🎖 Honors and Awards

  • SDM Student Travel Award, City University of Hong Kong
  • Research Tuition Scholarship, City University of Hong Kong
  • UGC Full PhD Scholarship, City University of Hong Kong
  • The First Academic Scholarship, University of Electronic Science and Technology of China
  • The First Prize of Graduate Admission Scholarship, University of Electronic Science and Technology of China
  • The Second Prize of UESTC Scholarship, University of Electronic Science and Technology of China (2 Times)
  • The Third Academic Scholarship, University of Electronic Science and Technology of China

📖 Educations

  • 2021.09 - Present, Ph.D. in Data Science, City University of Hong Kong, Hong Kong SAR Supervisors: Prof. Xiangyu Zhao, Dr. Ruochen Guo (External) and Prof. Junhui Wang (External)
  • 2018.09 - 2021.06, M.Phil. in Computer Science, University of Electronic Science and Technology of China, Chengdu, China Supervisor: Prof. Zenglin Xu
  • 2014.09 - 2018.06, B.E. in Computer Science (Yingcai Honors College), University of Electronic Science and Technology of China, Chengdu, China Supervisor: Prof. Zenglin Xu

💬 Services

  • 2024.04, Session Chair, The Web Conference (WWW)

    Chair of “Specialized Innovations in Recommender Systems” and “User Modeling for Recommenders” sessions

  • 2024-2025, Program Committee Member and Conference Reviewer,

    PC Member: WWW 2025 (Demo Track), CIKM 2024, PAKDD 2025, CIKM 2025

    Reviewer: NeurIPS 2024, KDD 2025, ICLR 2025, AISTATS 2025, ICML 2025, SIGIR 2025, NeurIPS 2025

  • 2020-2025, Journal Reviewer,

    IEEE TNNLS, IEEE Trans. on Big Data, Neural Networks, Neurocomputing, ACM TKDD, IEEE JSAC, Scientific Reports

💻 Internships

  • 2024.06 - 2025.03, Research Intern, Alipay Department, Ant Group, Hangzhou, China Research on Large Language Models and function calling techniques, focusing on intelligent agent systems development
  • 2023.06 - 2024.06, Research Intern, CTO Research Department, Ant Group, Hangzhou, China
    • Developed LLM distillation and pruning techniques for advertising: 5x speed-up, 50% energy reduction, 0.8% performance loss
    • Deployed NLU models for 10+ Alipay recommendation scenarios: 20x data processing speed, 5% PVCTR improvement
    • Built multimodal agent solution with Shanghai General Hospital for LLM-based medical case generation
  • 2019.06 - 2019.10, Research Intern, Peng Cheng Laboratory, Shenzhen, China Conducted research on quantum computing fundamentals and tensor network applications under Dr. Shenggen Zheng’s supervision at PCL Star Cloud Data Service Platform