WANG, Junhui 王軍輝

Position Chair
Email junhuiwang [at] cuhk.edu.hk
ORCiD 0000-0002-9165-5664
Phone Number 3943 3167
Fax Number 2603 5188
Address LSB 126
Homepage https://sites.google.com/site/junhuiwang

Academic Background

B.S. in Probability and Statistics, Peking University
Ph.D. in Statistics, University of Minnesota

Research Interest

Selected Publications

  1. Zhao, R., Zhang, H. and Wang, J. (2024+). Identifiability and consistent estimation for Gaussian chain graph models. Journal of the American Statistical Association, in press.
  2. Zhang, J., Wang, J. and Wang, X. (2024+). Consistent community detection in inter-layer dependent multi-layer networks. Journal of the American Statistical Association, in press.
  3. Xu, Q., Yuan, Y., Wang, J. and Qu, A. (2024). Crowdsourcing utilizing subgroup structure of latent factor modeling. Journal of the American Statistical Association, 119, 1192-1204.
  4. Zhen, Y. and Wang, J. (2023). Community detection in general hypergraph via graph embedding. Journal of the American Statistical Association, 118, 1620-1629.
  5. Zhang, J. , He, X. and Wang, J. (2022). Directed community detection with network embedding. Journal of the American Statistical Association, 117, 1809-1819.
  6. Zhao, R., He, X. and Wang, J. (2022). Learning linear non-Gaussian directed acyclic graph with diverging number of nodes. Journal of Machine Learning Research, 23(269):1-34.
  7. Feng, L. and Wang, J. (2022). Projected robust PCA with application to smooth image recovery. Journal of Machine Learning Research, 23(249):1-41.
  8. Dai, B. , Shen, X. and Wang, J. (2022). Embedding learning. Journal of the American Statistical Association, 117, 307-319.
  9. Dai, B. , Shen, X. , Wang, J. and Qu, A. (2021). Scalable collaborative ranking for personalized prediction. Journal of the American Statistical Association, 116, 1215-1223.
  10. Dai, B. , Wang, J. , Shen, X. and Qu, A. (2019). Smooth neighborhood recommender systems. Journal of Machine Learning Research, 20(16): 1-24.
  11. Bi, X. , Qu, A. , Wang, J. and Shen, X. (2017). A group-specific collaborative recommender. Journal of the American Statistical Association, 112, 1344-1353.
  12. Wang, J. , Shen, X. , Sun, Y. and Qu, A. (2017). Automatic summarization by existing and novel tags. Biometrika, 104, 273-290.
  13. Wang, J. , Shen, X. , Sun, Y. and Qu, A. (2016). Classification with unstructured predictors and an application to sentiment analysis. Journal of the American Statistical Association, 111, 1242-1253.
  14. Yang, L. , Lv, S. and Wang, J. (2016). Model-free variable selection in reproducing kernel Hilbert space. Journal of Machine Learning Research, 17(78): 1-24.
  15. Sun, W. , Wang, J. and Fang, Y. (2013). Consistent selection of tuning parameters in high-dimensional penalized regression. Journal of Machine Learning Research, 14, 3419-3440.
  16. Wang, J. (2010). Consistent selection of the number of clusters via cross validation. Biometrika, 97, 893-904.
  17. Wang, J. , Shen, X. and Pan, W. (2009). On large margin hierarchical classification with multiple paths. Journal of the American Statistical Association, 104, 1213-1223.
  18. Wang, J. , Shen, X. and Pan, W. (2008). On efficient large margin semisupervised learning: methodology and theory. Journal of Machine Learning Research, 10, 719-742.
  19. Wang, J. , Shen, X. and Liu, Y. (2008). Probability estimation for large margin classifiers. Biometrika, 95, 149-167.
  20. Wang, J. and Shen, X. (2007). Large margin semi-supervised learning. Journal of Machine Learning Research, 8, 1867-1891.

Major Research Grants

  1. RGC GRF-14303424 “Transfer graph learning: general framework and data-driven algorithms”, PI, 2025-2027
  2. RGC GRF-14306523 “Chain graph model: identifiability, estimation and asymptotics”, PI, 2024-2026
  3. RGC GRF-11311022 “A statistical framework for structure-preserving embedding of signed networks”, PI, 2023-2025
  4. RGC GRF-11301521 “Joint modeling of hypergraph networks for community detection and graph embedding”, PI, 2022-2024
  5. RGC GRF-11304520 “Hierarchical modeling of directed acyclic graphs: estimation, selection and asymptotics”, PI, 2021-2023
  6. RGC GRF-11300919 “Latent factor modeling of large-scale directed networks with covariates and structures”, PI, 2020-2022
  7. RGC GRF-11303918 “Scalable kernel-based variable selection with theoretical guarantee”, PI, 2019-2021
  8. RGC GRF-11331016 “Large-scale multi-label classification and its application to unstructured text data”, PI, 2017-2019
  9. RGC GRF-11302615 “Model-free variable selection via learning gradients”, PI, 2016-2018

Professional Services

  • Panel Member, HK RGC Physical Sciences Panel (JRS), since 2022
  • Associate Editor, Journal of the American Statistical Association – T&M, since 2023
  • Associate Editor, Journal of Computational and Graphical Statistics, since 2024
  • Associate Editor, Annals of Applied Statistics, since 2023
  • Associate Editor, Statistica Sinica, since 2020
  • Associate Editor, Statistics and Its Interface, since 2017
  • Associate Editor, Annals of the Institute of Statistical Mathematics, 2018-2024
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