C. Lee and M. Wang. Beyond the Signs: Nonparametric tensor completion via sign series. Advances in Neural Information Processing Systems 34 (NeurIPS). 2021. [Preprint] [Software]

Brown bag talk at IFDS UW-Madison, 2021. Invited conference talk at Eastern North American Region (ENAR). Invited talk at University of Haifa in Israel, forthcoming.

J. Hu, C. Lee, and M. Wang. Generalized Tensor Decomposition with features on multiple modes. Journal of Computational and Graphical Statistics, 2021 [Journal] [Conerence version] [Preprint] [Software]

This work wins Best Student Paper Award from the Statistical Computing and Graphics Section of American Statistical Association (ASA), 2021.

Part of the work is accepted into Advances in Neural Information Processing Systems 33 (NeurIPS) Second Workshop on Machine Learning and the Physical Sciences, 2020.

C. Lee and M. Wang. Tensor denoising and completion based on ordinal observations. Proceedings of International Conference on Machine Learning (ICML), PMLR 119:5778-5788, 2020. [Journal] [Preprint] [Software]

Invited conference talk at Eastern North American Region (ENAR), International Biometric Society, 2020. Invited conference talk at ICSA Applied Statistics Symposium, 2020.

M. Wang and L. Li. Learning from Binary Multiway Data: Probabilistic Tensor Decomposition and Its Statistical Optimality. Journal of Machine Learning Research, 21(154): 1−38, 2020. [Journal] [Preprint] [Software]

Invited department talks at UChicago (Stats), Stanford (Stats), Society for Industrial and Applied Mathematics (SIAM) annual meeting, Potland; Bosch Center for Artificial Intelligence, Sunnyvale, California; Systems, Information, Learning and Optimization (SILO) Talk at UW-Madison, 2019

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]

Invited department talk at Columbia, 2020. Institute of Foundation of Data Science (IFDS) brown-bag at UW-Madison. Invited talks at 2019 International Conference on Frontiers of Data Science, 2019 Institute of Mathematical Statistics (IMS) meeting at China.

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]

Invited department talks at Stanford (Stats), UC Berkeley (Biostats). Platform Talk at Computational and Genomic Biology Retreat at UC Berkeley. Computation and Informatics in Biology and Medicine (CIBM) at UW-Madison, 2019.

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]

Attention score in the top 5% of all research articles ever tracked by Altmetric (as of June 2018) ; Higher than 89% of the research articles published in PNAS.

Platform talk (top 13%) at the 2nd Probabilistic Modeling in Genomics, Cold Spring Harbor Laboratory, NY.

Invited talk at the 2019 European Society for Evolutionary Biology-Special Topic Networks workshop at Germany.

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]

Invited department talks at CMU (Stats & Data Science), UW-Madison (Stats), Columbia (Stats), UToronto (Stats), Johns Hopkins (Biostats).

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]

Invited Department Colloquium Talk at Duke (Stats), Boston University (Math), UMass-Amherst (Applied Math), Queen's (Math), and JSM16.

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]

Highlighted as Editor’s Pick Paper of this issue.

For part of this work, I was named a semifinalist for the ASHG Charles J. Epstein Trainee Award (27 predoctoral recipients out of 550 candidates) for Excellence in Human Genetics Research; Also invited to give a platform talk (top 8%) in 2014 Annual Meeting of American Society of Human Genetics.

For a different part of this work, I was named a finalist for the IGES Williams Award (3 out of 156) for Best Platform Presentation by a Graduate Student; Also invited to give one of the six talks in Neels and Williams Awards Session in 2013 Annual Meeting of the International Genetic Epidemiology Society.

National Science Foundation (NSF) CAREER DMS-2141865, $400K, sole PI, 2022-2026.

National Science Foundation (NSF) EF-2133740, co-Principle Investigator (PI) together with Daniel I Bolnick (PI) and Tina Eliassi-Rad (co-PI), 3 million in total, 2022-2026.

National Science Foundation (NSF) DMS-1915978, $180K, sole PI, 2019-2022.

Fall Research Competition, Wisconsin Alumni Research Foundation, $40K/year, sole PI, 2020-2022 (three times).

ICML Diversity and Inclusion Fellowship, 2020.

Institute of Mathematical Statistics (IMS) New Researcher Travel Award, 2020-2021.

NeurIPS Junior Researcher 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, 2019.