Academic Background
B.S. in Probability and Statistics, Peking University
Ph.D. in Statistics, University of Minnesota
Research Interest
Selected Publications
- 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.
- 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.
- 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.
- Zhen, Y. and Wang, J. (2023). Community detection in general hypergraph via graph embedding. Journal of the American Statistical Association, 118, 1620-1629.
- Zhang, J. , He, X. and Wang, J. (2022). Directed community detection with network embedding. Journal of the American Statistical Association, 117, 1809-1819.
- 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.
- Feng, L. and Wang, J. (2022). Projected robust PCA with application to smooth image recovery. Journal of Machine Learning Research, 23(249):1-41.
- Dai, B. , Shen, X. and Wang, J. (2022). Embedding learning. Journal of the American Statistical Association, 117, 307-319.
- 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.
- Dai, B. , Wang, J. , Shen, X. and Qu, A. (2019). Smooth neighborhood recommender systems. Journal of Machine Learning Research, 20(16): 1-24.
- Bi, X. , Qu, A. , Wang, J. and Shen, X. (2017). A group-specific collaborative recommender. Journal of the American Statistical Association, 112, 1344-1353.
- Wang, J. , Shen, X. , Sun, Y. and Qu, A. (2017). Automatic summarization by existing and novel tags. Biometrika, 104, 273-290.
- 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.
- 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.
- 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.
- Wang, J. (2010). Consistent selection of the number of clusters via cross validation. Biometrika, 97, 893-904.
- 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.
- 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.
- Wang, J. , Shen, X. and Liu, Y. (2008). Probability estimation for large margin classifiers. Biometrika, 95, 149-167.
- Wang, J. and Shen, X. (2007). Large margin semi-supervised learning. Journal of Machine Learning Research, 8, 1867-1891.
Major Research Grants
- RGC GRF-14303424 “Transfer graph learning: general framework and data-driven algorithms”, PI, 2025-2027
- RGC GRF-14306523 “Chain graph model: identifiability, estimation and asymptotics”, PI, 2024-2026
- RGC GRF-11311022 “A statistical framework for structure-preserving embedding of signed networks”, PI, 2023-2025
- RGC GRF-11301521 “Joint modeling of hypergraph networks for community detection and graph embedding”, PI, 2022-2024
- RGC GRF-11304520 “Hierarchical modeling of directed acyclic graphs: estimation, selection and asymptotics”, PI, 2021-2023
- RGC GRF-11300919 “Latent factor modeling of large-scale directed networks with covariates and structures”, PI, 2020-2022
- RGC GRF-11303918 “Scalable kernel-based variable selection with theoretical guarantee”, PI, 2019-2021
- RGC GRF-11331016 “Large-scale multi-label classification and its application to unstructured text data”, PI, 2017-2019
- 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