Below is a list of my publications: click through the linked title for more details.

R. B. Lehoucq,

**M. Weylandt**, and J. W. Berry. “Optimal accuracy for linear sets of equations with the graph Laplacian”. 2024.C. O. Little†,

**M. Weylandt**† and G. I. Allen. “To the Fairness Frontier and Beyond: Identifying, Quantifying, and Optimizing the Fairness-Accuracy Pareto Frontier”. 2022.**M. Weylandt**and G. Michailidis. “Multivariate Analysis for Multiple Network Data via Semi-Symmetric Tensor PCA”. 2022.**M. Weylandt**and G. I. Allen. “Debiasing Projections for Fair Principal Components Analysis”. 2021.M. Navarro, G. I. Allen, and

**M. Weylandt**. “Network Clustering for Latent State and Changepoint Detection”. 2021.**M. Weylandt**, Y. Han, and K. B. Ensor. “Multivariate Modeling of Natural Gas Spot Trading Hubs Incorporating Futures Market Realized Volatility”. 2019.Winner of the

*ASA Section on Business and Economic Statistics (B&E) 2020 Student Paper Competition*A.P. Drager,

**M. Weylandt**, G. Chuyong, D. Kenfack, D.W. Thomas, and A.E. Dunham. “Ecological correlates of reproductive status in a guild of Afrotropical understory trees.” 2019.

**M. Weylandt**and L. P. Swiler. “Beyond PCA: Additional Dimension Reduction Techniques to Consider in the Development of Climate Fingerprints.”*Journal of Climate*37(5), pp.1723-1735. 2024.**M. Weylandt**, G. Michailidis, and T. M. Roddenberry. “Sparse Partial Least Squares for Coarse Noisy Graph Alignment.”*SSP 2021: Proceedings of the 2021 IEEE Statistical Signal Processing Workshop 2021*, pp.561-565. 2021.**M. Weylandt**, T.M. Roddenberry, and G. I. Allen. “Simultaneous Grouping and Denoising via Sparse Convex Wavelet Clustering.”*DSLW 2021: Proceedings of the IEEE Data Science and Learning Workshop 2021*. pp.1-8. 2021.**M. Weylandt**and G. Michailidis. “Automatic Registration and Clustering of Time Series.”*ICASSP 2021: Proceedings of the 2021 IEEE International Conference on Acoustics, Speech and Signal Processing*, pp.5609-5613. 2021.J.S. Morris, M.M. Hassan, Y.E. Zohner, Z. Wang, L. Xiao, A. Rashid, A. Haque, R. Abdel-Wahad, Y.A. Mohamed, K.L. Ballard, R.A. Wolff, B. George, L. Li, G. I. Allen,

**M. Weylandt**, D. Li, W. Wang, K. Raghav, J. Yao, H.M. Amin, and A.O. Kaseb. “HepatoScore‐14: Measures of biological heterogeneity significantly improve prediction of hepatocellular carcinoma risk.”*Hepatology*73(6), pp. 2278-2292. 2021.**M. Weylandt.**“Multi-Rank Sparse and Functional PCA: Manifold Optimization and Iterative Deflation Techniques.”*CAMSAP 2019: Proceedings of the IEEE 8th International Workshop on Computational Advances in Multi-Sensor Adaptive Processing*, pp.500-504. 2019.**M. Weylandt**, J. Nagorski, and G. I. Allen. “Interactive Visualizations and Fast Computation for Convex Clustering via Algorithmic Regularization.”*Journal of Computational and Graphical Statistics*29(1), pp. 87-96. 2020.Winner of the

*ASA Section on Statistical Learning and Data Science (SLDS) 2019 Student Paper Competition***M. Weylandt**. “Splitting Methods for Convex Bi-Clustering and Co-Clustering.”*DSW 2019: Proceedings of the IEEE Data Science Workshop 2019*, pp.237-244. 2019.G. I. Allen and

**M. Weylandt**. “Sparse and Functional Principal Components Analysis.”*DSW 2019: Proceedings of the IEEE Data Science Workshop 2019*, pp.11-16. 2019.

**M. Weylandt.**“Computational and Statistical Methodology for Highly-Structured Data.”*Ph.D. Thesis, Rice University*. 2020.L. Damiano, B. Peterson, and

**M. Weylandt**. “A Tutorial on Hidden Markov Models using Stan.”*StanCon 2018*.

A BibTeX file for these publications can be found here.