• C. Lee and M. Wang. Tensor denoising and completion based on ordinal observations. Under review, 2020. [arXiv] [Software]


  • Z. Xu*, J. Hu*, and M. Wang. Generalized tensor regression with covariates on multiple modes. *equal contribution. Under review, 2019. [arXiv] [Software]

  • M. Wang and L. Li. Learning from Binary Multiway Data: Probabilistic Tensor Decomposition and Its Statistical Optimality. Revision submitted to the Journal of Machine Learning Research. 2019. [arXiv]


  • M. Wang and Y. Zeng. Multiway clustering via tensor block models. Advances in Neural Information Processing Systems 32 (NeurIPS), 715-725, 2019. [Journal] [Preprint] [Software]


  • M. Wang, J. Fischer, and Y. S. Song. Three-way Clustering of Multi-tissue Multi-individual Gene Expression Data Using Semi-nonnegative Tensor Decomposition. Annals of Applied Statistics. Vol. 13, No. 2, 1103-1127, 2019. [Journal] [Preprint] [Supplementary] [Software: Multi-Cluster]


  • M. Wang, F. Roux, C. Bartoli, C. H.-Chauveau, C. Meyer, H. Lee, D. Roby, M. S. McPeek, and J. Bergelson. Two-way Mixed-Effects Methods for Joint Association Analyses Using Both Host and Pathogen Genomes. Proc. Natl. Acad. Sci. (direct submission). Vol. 115 (24), E5440-E5449, 2018. [Journal] [Typesetting error in the published version] [Supplementary] [Software: ATOMM]


  • D. Jiang and M. Wang. Recent Developments in Statistical Methods for GWAS and High-throughput Sequencing Studies of Complex Traits. Biostatistics and Epidemiology. Vol. 2 (1), 132-159, 2018. [Journal]

  • M. Wang and Y. S. Song. Tensor Decomposition via Two-Mode Higher-Order SVD (HOSVD). Journal of Machine Learning Research W & CP (AISTATS track), Vol. 54, 614-622, 2017. [Journal] [Supplementary] [Preprint] [Software: TM-HOSVD]


  • M. Wang, K. Dao Duc, J. Fischer, and Y. S. Song. Operator Norm Inequalities Between Tensor Unfoldings on the Partition Lattice. Linear Algebra and its Applications, Vol. 520, 44-66, 2017. [Journal] [Preprint]

  • M. Wang , J. Jakobsdottir, A. V. Smith, and M. S. McPeek. G-STRATEGY: Optimal Selection of Individuals for Sequencing in Genetic Association Studies. Genetic Epidemiology, Vol. 40, No. 6, 446–460, 2016. [Journal] [Software: G-STRATEGY]

  • Institute of Mathematical Statistics (IMS) New Researcher Travel Award, 2021.

    National Science Foundation (NSF) DMS-1915978 (sole PI), 2019-2022.

    Fall Research Competition (sole PI), Wisconsin Alumni Research Foundation, 2020-2021.

    NIPS travel award, 2019.

    Google Cloud Platform Education Grants. Free clound computing credits to students in class, 2019.

    Vice Chancellor for Research and Graduate Education (VCRGE) Travel Award, UW-Madison.