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Boris Landa

I am an Associate Research Scientist in the Applied Mathematics Program at Yale University, where my research focuses on developing theoretical and computational tools for processing and analyzing large datasets. Specifically, I am interested in the challenges associated with extracting low-dimensional structures under complex noise and deformations commonly found in experimental data. Notable applications of my current and past research include the analysis of single-cell RNA sequencing data and molecular reconstructions in electron microscopy.

Selected preprints and publications

Boris Landa and Yuval Kluger. "The Dyson Equalizer: Adaptive Noise Stabilization for Low-Rank Signal Detection and Recovery". arXiv
Boris Landa and Xiuyuan Cheng. "Robust Inference of Manifold Density and Geometry by Doubly Stochastic Scaling". SIAM Journal on Mathematics of Data Science (2023). arXiv. DOI.
Boris Landa, Thomas T.C.K. Zhang, Yuval Kluger. "Biwhitening Reveals the Rank of a Count Matrix". SIAM Journal on Mathematics of Data Science 4, no. 4 (2022): 1420-1446. arXiv. DOI.
Boris Landa, Ronald R.Coifman, Yuval Kluger. "Doubly Stochastic Normalization of the Gaussian Kernel is Robust to Heteroskedastic Noise". SIAM Journal on Mathematics of Data Science 3 (1), 388-413 (2021). DOI. arXiv.
Boris Landa and Yoel Shkolnisky. "Multi-reference factor analysis: low-rank covariance estimation under unknown translations". Information and Inference: A Journal of the IMA 10, no. 3 (2021): 773-812. DOI. arXiv.
Boris Landa and Yoel Shkolnisky. "The Steerable Graph Laplacian and its Application to Filtering Image Datasets." SIAM Journal on Imaging Sciences, 11(4):2254--2304, 2018. DOI. arXiv.