Ilya V. Schurov

Ilya V. Schurov

Mathematics, ML & AI

Radboud University

About me

I’m a mathematician, ML researcher and technology enthusiast. I love pure mathematics and I equally love to code and solve applied problems. Currently I work at Radboud University in the Theory of Condensed Matter group. Previously I worked as an associate professor at HSE University, where I participated in various research projects with topics ranging from differential equations and physics to game theory to linguistics. My teaching experience include courses on calculus, machine learning, differential equations and data science. I prepared several online courses for Coursera devoted to foundations of machine learning and wrote free interactive textbooks on calculus and ordinary differential equations that are used by thousands Russian-speaking students.

Download my CV.

Interests
  • Machine Learning
  • Differential Equations
  • Dynamical Systems
Education
  • Ph.D. in Mathematics, 2010

    Moscow State University

  • M.S. in Mathematics, 2006

    Moscow State University

Textbooks

I want to reinvent mathematical textbooks: make them accessible, friendly, full of illustrations and in-depth explanations of the essence of mathematical concepts. To achieve this goal, I even developed my own publishing platform that leverages modern web-technologies and allows to include interactive elements to mathematical texts.

Calculus
Friendly introduction to rigorous one-dimensional calculus. We have precise epsilon-delta definitions and all the proofs, carefully explained, with examples, motivations and illustrations. Batteries included!
Ordinary differential equations
Introductory textbook with focus on important geometrical and dynamical phenomena like conservation laws, stability and bifurcations.

Research Papers

(2024). Long range segmentation of prokaryotic genomes by gene age and functionality. Nucleic Acids Research.

Cite DOI URL

(2024). Invariant multiscale neural networks for data-scarce scientific applications.

Cite arXiv URL

(2022). Can Recall Data Be Trusted?. Field Methods, 34 (4), 2022.

Cite DOI Code

(2020). Bachet’s game with lottery moves. Discrete Mathematics, 343 (4), 111704.

Cite DOI arXiv