
Randomized numerical linear algebra · high-dimensional probability · stochastic optimization · robust iterative methods · tensor methods
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Short CV (2025) · arXiv · elre@princeton.edu
Last updated: June 2026
My research is in randomized numerical linear algebra and the mathematics of data science, with close connections to high-dimensional probability and stochastic optimization. I am interested in mathematically justified and effective randomized algorithms for large-scale data problems, especially in settings where the data or the problem has non-trivial mathematical structure, such as spectral decay, multimodality, nonnegativity, tensor structure, or structured noise.
My paper "On trimming tensor-structured measurements and efficient low-rank tensor recovery" was accepted to Linear Algebra and its Applications this summer.
This work has been supported by:
I also serve as an Associate Editor for Information and Inference: A Journal of the IMA.
At Princeton, I have taught:
Earlier teaching:
My first name is the Russian version of Elizabeth. I like all versions of my name: please call me Liza, Lisa, Eliza, or Elizabeth, whatever you like the best. In case you were curious, Elizaveta is pronounced approximately as "Ye (like in yellow) - lee - zuh - VYE - tuh". Standard pronunciation of Liza is "LEE - zuh".
My non-mathy interests include things that I find beautiful or challenging, such as, good stories, arts, oceans, mountains and cities, also finding and making perfect coffee. I also immensely enjoy long conversations with my six-year-old son, currently fascinated by the Jedi, whose curious and very sharp logic is so fun to follow.
“Poirot,” I said. “I have been thinking.”
“An admirable exercise my friend. Continue
it.”
(Agatha Christie, Peril at End House)