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Please feel free to drop me an email for some discussion or collaboration.

I am a principle researcher at Huawei. I received the B.S. degree in Automation from the University of Science and Technology of China, and the Ph.D. degree from Industrial Systems Engineering and Management Department, National University of Singapore, respectively. My research interests include pattern mining and machine learning, and their applications in multimodal data. I am also possoniate in music, dance and various sports, e.g., diving, hiking & badminton.

Contact:       zhoum1900@163.com
Links:      Google Scholar     ORCID


News

Publications

    Conference

  1. W.Qin, W.Bao,J.Wang, M.Zhou,.Double Queue for Constrained Online Convex Optimization: Bridging the Best-of-Two-Worlds Constraint Violations. INFOCOM, 2026. [PDF]
  2. C Wang, S Wang, ..., M.Zhou.Predicting DRAM Failures at Scale: A Two-Stage Approach for Heterogeneous Systems. HPCA, 2026. [PDF]
  3. L Yan, S Zhang, B Li, M.Zhou, Z Huang.Geometric Imbalance in Semi-Supervised Node Classification. NeurIPS, 2025. [PDF]
  4. H Xie, M.Zhou, Q Yu, J Yu, Z Sheng, H Xie, D Lian.M -MFP: A Multi-Scale and Multi-Level Memory Failure Prediction Framework for Reliable Cloud Infrastructure. KDD 2025. [PDF]
  5. M.Zhou, H Xie, Q Yu, J Yu, Z Sheng. SmartMem: Memory Failure Prediction Challenge at WWW 2025. Companion Proceedings of the ACM on Web Conference 2025, 3003‑3007. [PDF]
  6. Z Guo, Q Sun, H Yuan, X Fu, M.Zhou, Y Gao, J Li.GraphMoRE: Mitigating Topological Heterogeneity via Mixture of Riemannian Experts. AAAI 2025. [PDF]
  7. J Han, S Feng, M.Zhou, X Zhang, YS Ong, X Li. Diffusion Model in Normal Gathering Latent Space for Time Series Anomaly Detection.ECML‑PKDD 2024. [PDF]
  8. T Yang, J Meng, M.Zhou, Y Yang, Y Wang, X Li, Y Tong.You Can't Ignore Either: Unifying Structure and Feature Denoising for Robust Graph Learning. CIKM 2024. [PDF]
  9. K Li, T Yang, M.Zhou, J Meng, S Wang, Y Wu, B Tan, H Song, L Pan, F Yu. SEFraud: Graph-based Self-Explainable Fraud Detection via Interpretative Mask Learning.KDD 2024. [PDF]
  10. Q Yu, W Zhang, M.Zhou, J Yu, Z Sheng, J Bogatinovski, J Cardoso, O Kao.Investigating Memory Failure Prediction Across CPU Architectures.DSN2024. [PDF]
  11. M.Zhou,B. Li, S.Zhang, M.Yang, D.Lian, Z.Huang.BSAL: A Framework of Bi-component Structure and Attribute Learning for Link Prediction. SIGIR, 2022. [PDF]
  12. M.Zhou, B. Li, M.Yang and L.Pan(2022) TeleGraph: A Benchmark Dataset for Hierarchical Link Prediction. GLB@ Webconf, 2022
  13. M. Yang, M.Zhou and et al. HRCF: Enhanced Collaborative Filter via Hyperbolic Geometric Regularization. Webconf, 2022.
  14. J. Liu, M.Zhou and et al. Discovering Representation Attribute-stars via Minimum Description Length. ICDE, 2022.
  15. J. Liu, M.Yang, M.Zhou and et al. Enhancing Hyperbolic Graph Embeddings via Contrastive Learning. SSL@Neurips, 2021
  16. M. Yang, M.Zhou and et al. Discrete-time Temporal Network Embedding via Implicit Hierarchical Learning.KDD, 2021.
  17. Z.Huang, S.Zhang, C.Xi, T.Liu and M.Zhou. Scaling Up Graph Neural Networks Via Graph Coarsening. KDD, 2021.[pdf]

    Journal

  1. S Zhang, Y Zhang, B Li, W Yang, M.Zhou, Z Huang. Neural Networks 183, 106931. [PDF]
  2. C Wu, D Lian, Y Ge, M.Zhou, E Chen. ACM Transactions on Knowledge Discovery from Data 18 (7), 1‑27. [PDF]
  3. J.Liu, F.Philippe, M.Zhou,and G.He.(2022)Discovering Compressing Stars in Attributed Graphs. Information Sciences.
  4. F‐V., Philippe, ..., M.Zhou, et al.(2020)A survey of pattern mining in dynamic graphs. Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery
  5. J. Hu, M.Zhou, X.Li and, Z.Xu. (2016) Online Model Regression for Nonlinear Time-varying Manufacturing Systems. Automatica .
  6. M.Zhou, T.N. Goh. (2016) Iterative Designed Experiment Analysis (IDEA). Quality and Reliability Engineering International. .
  7. M.Zhou, T.N. Goh. (2015) Effects of Model Accuracy on Residual Control Charts. Quality and Reliability Engineering International. .

Activities

  • Section Chair, DataFun GNN Summit 2022
  • CO-organizer, MLiSE(Machine Learning for System Engineering) Workshop@ECML-PKDD 2021
  • Mentor, SDSC 6002 Research Projects for Data Science , City University of HongKong, Winter 2019, 2020
  • Reviewer @ ICML 2022,KDD 2022 and ECML-PKDD2022, 2021
  • Technical committee member and Session Chair@Asian Network for Quality Winter 2014

Projects

    TBA

Links

    TBA