Maolin Wang is a Ph.D. candidate at City University of Hong Kong under the supervision of Prof. Xiangyu Zhao and co-supervision of Dr. Ruocheng Guo and Prof. Junhui Wang. His research focuses on graph learning, model compression, tensor/matrix decomposition, and LLMs. 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

  • 2025.05: 🎉🎉 As one of his mentors, I am proud that Xuhui Chen has been awarded the Outstanding Academic Performance Award (Top 2/200).
  • 2025.05: 🎉🎉 The representative work from my PhD period, Put Teacher in Student’s Shoes: Cross-Distillation for Ultra-compact Model Compression Framework (EI-BERT), has been accepted by KDD 2025. Now, the 1.9 MB-sized EI-BERT has become a fundamental capability in Alipay.
  • 2025.05: 🎉🎉 As one of their mentors, I am proud that Tianshuo Wei, Xuhui Chen, Yanxin Chen, and Linjie Mi have been awarded the Outstanding Performance Award.
  • 2025.05: 🎉🎉 Our two papers have been accepted by ACL 2025 (1 for Findings and 1 for Main)!
  • 2025.05: 🎉🎉 Our three papers have been accepted by KDD 2025 (Research Track)!
  • 2025.05: 🎉🎉 As one of his mentors, I am proud that Tianshuo Wei has been awarded the Outstanding Dissertation Award.
  • 2025.05: 🎉🎉 Our LLM-enhanced Recommender Systems Tutorial and Survey has been accepted by KDD 2025 (Survey Track).
  • 2025.05: 🎉🎉 Our paper DANCE: Resource-Efficient Neural Architecture Search with Data-Aware and Continuous Adaptation has been accepted by IJCAI 2025!
  • 2025.04: 🎉🎉 Our two papers have been accepted by SIGIR 2025!
  • 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

Conference Papers

[C22] ​​Maolin Wang, Jun Chu, Sicong Xie, Xiaoling Zang, Yao Zhao, Wenliang Zhong, Xiangyu Zhao. (2025). Put Teacher in Student’s Shoes: Cross-Distillation for Ultra-compact Model Compression Framework. In SIGKDD Conference on Knowledge Discovery and Data Mining (KDD) (CCF-A) [Deployed in 10+ real-world scenarios at Ant Group and Alipay].

[C21] Jingyu Peng, Maolin Wang, Xiangyu Zhao, Kai Zhang, Wanyu Wang, Pengyue Jia, Qidong Liu, Ruocheng Guo, Qi Liu. (2025). Stepwise Reasoning Error Disruption Attack of LLMs. In Annual Meeting of the Association for Computational Linguistics (ACL) (CCF-A).

[C20] Pengyue Jia, Derong Xu, Xiaopeng Li, Zhaocheng Du, Xiangyang Li, Yichao Wang, Yuhao Wang, Qidong Liu, Maolin Wang, Huifeng Guo, Ruiming Tang, Xiangyu Zhao. (2025). Bridging Relevance and Reasoning: Rationale Distillation in Retrieval-Augmented Generation. In Findings of Annual Meeting of the Association for Computational Linguistics (ACL).

[C19] Maolin Wang, Yutian Xiao, Binhao Wang, Sheng Zhang, Shanshan Ye, Wanyu Wang, Hongzhi Yin, Ruocheng Guo, Zenglin Xu. (2025). FLUID-MMRec: Stein-Guided Entropic Flow for Multi-Modal Sequential Recommendation. In SIGKDD Conference on Knowledge Discovery and Data Mining (KDD) (CCF-A).

[C18] Yi Wen, Yue Liu, Derong Xu, Huishi Luo, Pengyue Jia, Yiqing Wu, Siwei Wang, KE LIANG, Maolin Wang, Yiqi Wang, Fuzhen Zhuang, Xiangyu Zhao. (2025). Measure Domain’s Gap: A Similar Domain Selection Principle for Multi-Domain Recommendation. In SIGKDD Conference on Knowledge Discovery and Data Mining (KDD) (CCF-A).

[C17] Yingyi Zhang, Pengyue Jia, Xianneng Li, Derong Xu, Maolin Wang, Yichao Wang, Zhaocheng Du, Huifeng Guo, Yong Liu, Ruiming Tang, Xiangyu Zhao. (2025). LSRP: A Leader–Subordinate Retrieval Framework for Privacy-Preserving Cloud–Device Collaboration. In SIGKDD Conference on Knowledge Discovery and Data Mining (KDD) (CCF-A).

[C16] Qidong Liu, Xiangyu Zhao, Yuhao Wang, Yejing Wang, Zijian Zhang, Yuqi Sun, Xiang Li, Maolin Wang, Pengyue Jia, Chong Chen, Wei Huang, Feng Tian. (2025). Large language model enhanced recommender systems: Taxonomy, Trend, Application, and Future. In Survey & Tutorial Track at SIGKDD Conference on Knowledge Discovery and Data Mining (CCF-A).

[C15] Maolin Wang, Tianshuo Wei, Sheng Zhang, Ruocheng Guo, Wangyu Wang, Shanshan Ye, Lixin Zou, Xuetao Wei, Xiangyu Zhao. (2025). DANCE: Resource-Efficient Neural Architecture Search with Data-Aware and Continuous Adaptation. In International Joint Conference on Artificial Intelligence (IJCAI) (CCF-A).

[C14] Maolin Wang, Sheng Zhang, Ruocheng Guo, Wanyu Wang, Xuetao Wei, Zitao Liu, Hongzhi Yin, Yi Chang, Xiangyu Zhao. (2025). STAR-Rec: Making Peace with Length Variance and Pattern Diversity in Sequential Recommendation. In International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR) (CCF-A).

[C13] Yuhao Wang, Junwei Pan, Pengyue Jia, Wanyu Wang, Maolin Wang, Zhixiang Feng, Xiaotian Li, Jie Jiang, Xiangyu Zhao. (2025). PAD: Large Language Models Enhancing Sequential Recommendation. In International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR) (CCF-A).

[C12] Maolin Wang, Xiangyu Zhao. (2025). MetaLoRA: Tensor-Enhanced Adaptive Low-Rank Fine-tuning. In PhD Symposium Track at IEEE International Conference on Data Engineering (ICDE).

[C11] 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 (KDD) (CCF-A).

[C10] 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).

[C9] 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].

[C8] 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 Industry Track at The Web Conference (WWW) [Oral] [Deployed in 5+ real-world scenarios at Ant Group and Alipay].

[C7] 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).

[C6] 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).

[C5] 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).

[C4] 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).

[C3] 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).

[C2] 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.

[C1] 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).

Journal Papers

[J2] Xiaopeng LI, Maolin Wang, and Hing Cheung So. (2022). An Interpretable Bi-Branch Neural Network for Matrix Completion. In Signal Processing (SCI-Q2).

[J1] Yu Pan, Maolin Wang, and Zenglin Xu. (2021). TedNet: A Pytorch Toolkit For Tensor Decomposition Networks. In Neurocomputing (SCI-Q2) [100+ stars in Github].

📝 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
  • 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,

    Senior PC Member: CIKM 2025 (Short Paper Track)

    PC Member: WWW 2025 (Demo Track), CIKM 2024, PAKDD 2025, CIKM 2025, GENNEXT@SIGIR’25

    Reviewer: NeurIPS 2024, KDD 2025, ICLR 2025, AISTATS 2025, ICML 2025, IEEE DSAA 2025, SIGIR 2025, NeurIPS 2025, ACMMM 2025

  • 2020-2025, Journal Reviewer,

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

👨‍🏫 Mentorships

Cityu HK Students Under My Supervision/Co-Supervision
Co-supervision with Prof. Xiangyu Zhao
City University of Hong Kong (2022-Present)

  • Tuohuan You (2024.12-)
  • Yanxin Chen (2024.12-) With Derong Xu, Outstanding Performance Award
  • Linjie Mi (2024.09-) With Yingyi Zhang, Outstanding Performance Award
  • Xuhui Chen (2024.09-) With Wenlin Zhang, Outstanding Performance Award and Outstanding Academic Performance Award
  • Binhao Wang (2024.09-) With Zichuan Fu
  • Zhiqi Li (2024.09-)
  • Tianshuo Wei (2024.09-) Outstanding Dissertation Award and Outstanding Performance Award
  • Bowen Yu (2024.09-) Next position - PhD student, AML Lab, City University of Hong Kong
  • Sheng Zhang (2023.09-2024.09) Outstanding Academic Performance Award, Outstanding Research Project Award, current position - Assistant Engineer, Chinese Academy of Sciences
  • Jie Wang (2022.09-2023.09) Outstanding Dissertation Award, current position - HK AIFT
  • Tong Wu (2022.09-2023.09) Current position - Kuaishou

💻 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