WANG, Junhui 王軍輝

Position Professor
ORCiD 0000-0002-9165-5664
Phone Number 3943 xxxx
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. Zhen, Y. and Wang, J. (2022+). Community detection in general hypergraph via graph embedding. Journal of American Statistical Association. In press.
  2. Zhang, J. , He, X. and Wang, J. (2022+). Directed community detection with network embedding. Journal of American Statistical Association. In press.
  3. Dai, B. , Shen, X. and Wang, J. (2022). Embedding learning. Journal of American Statistical Association, 117, 307-319.
  4. 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.
  5. Dai, B. , Wang, J. , Shen, X. and Qu, A. (2019). Smooth neighborhood recommender systems. Journal of Machine Learning Research, 20(16), 1 – 24.
  6. Bi, X. , Qu, A. , Wang, J. and Shen, X. (2017). A group-specific collaborative recommender. Journal of the American Statistical Association, 112, 1344 – 1353.
  7. Wang, J. , Shen, X. , Sun, Y. and Qu, A. (2017). Automatic summarization by existing and novel tags. Biometrika, 104, 273 – 290.
  8. 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.
  9. 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.
  10. 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.
  11. Wang, J. (2010). Consistent selection of the number of clusters via cross validation. Biometrika, 97, 893 – 904.
  12. 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.
  13. 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.
  14. Wang, J. , Shen, X. and Liu, Y. (2008). Probability estimation for large margin classifiers. Biometrika, 95, 149 – 167.
  15. 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-11301521 “Joint modeling of hypergraph networks for community detection and graph embedding”, PI, 2022-2024
  2. RGC GRF-11304520 “Hierarchical modeling of directed acyclic graphs: estimation, selection and asymptotics”, PI, 2021-2023
  3. RGC GRF-11300919 “Latent factor modeling of large-scale directed networks with covariates and structures”, PI, 2020-2022
  4. RGC GRF-11303918 “Scalable kernel-based variable selection with theoretical guarantee”, PI, 2019-2021
  5. RGC GRF-11331016 “Large-scale multi-label classi cation and its application to unstructured text data”, PI, 2017-2019
  6. RGC GRF-11302615 “Model-free variable selection via learning gradients”, PI, 2016-2018

Professional Services

  • Panel Member, HK RGC Physical Sciences Panel (JRS)
  • Associate Editor, Statistica Sinica
  • Associate Editor, Annals of Institute of Statistical Mathematics
  • Associate Editor, Statistics and Its Interface