Anastasia Kireeva

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Email: firstname.lastname@math.ethz.ch

Office: HG G 21.2

About

I am a final year PhD student at ETH Zurich working with Prof. Afonso Bandeira at Mathematics Department. My research interests include high-dimensional statistics, computational complexity, and randomized algorithms. In particular, I work on understanding of phase transitions and computational hardness of statistical inference.

I am passionate about teaching mathematics and finding methods for making learning process more efficient in higher education. Here is a D-MATH article about the puzzle technique I introduced to a student seminar to make it more interactive. Please refer to the teaching section below to learn more about my teaching at ETH.

Here is a link to my full CV (last updated in July 2026).

Teaching

  • Spring 2025

    Randomized matrix computations

    Lecturer

  • Fall 2024 and Spring 2026

    Average-case complexity in statistical inference

    Organizer of the Student seminar in jigsaw format

  • Fall 2023 and 2026

    Mathematics of Data Science

    Course Coordinator

  • Spring 2023 and 2024

    Mathematics of Signals, Networks, and Learning Category

    Teaching Assistant

  • Fall 2022

    Mathematics of Data Science

    Teaching Assistant

Selected publications

  • Computational lower bounds for multi-frequency group synchronization

    Anastasia Kireeva, Afonso S. Bandeira, Dmitriy Kunisky (2026)

    arXiv| Publication| Poster
  • The Lovász number of random circulant graphs

    Afonso S. Bandeira, Jarosław Błasiok, Daniil Dmitriev, Ulysse Faure, Anastasia Kireeva, Dmitriy Kunisky (2025)

    arXiv| Publication
  • Randomized matrix computations: Themes and variations

    Anastasia Kireeva, Joel Tropp (2024)

    arXiv
  • Breakdown of a concavity property of mutual information for non-Gaussian channels

    Anastasia Kireeva, Jean-Christophe Mourrat (2023)

    Information and Inference: A Journal of the IMA 13.2
    arXiv | Publication | Poster
  • Stochastic Policy Gradient Methods: Improved Sample Complexity for Fisher-non-degenerate Policies

    Ilyas Fatkhullin, Anas Barakat, Anastasia Kireeva, Niao He (2023)

    International Conference on Machine Learning. PMLR, pp. 9827–9869
    arXiv | Publication | Code | Poster