About
Hello, dear visitor!
My name is Gleb Karpov and I am a researcher in the field of applied mathematics, and university lecturer in related fields. On the professional side I have worked on numerical linear algebra, fast matrix factorizations, uncertainty quantification, and surrogate modeling of computationally expensive models. Nowadays I focus on machine learning for telecommunications and signal processing.
In parallel, since 2021 I have been teaching at HSE University in Moscow. Now I give lectures on probability & statistics and linear algebra in flagship programs at the Graduate School of Business and in a Master’s program at the Faculty of Computer Science, both in russian and english, especially enjoing the latter.
Teaching has been with me since my first year of university: for many years I taught at a summer school for high-school students. Along the way I realized I can build emotionally engaging stories without the dry style of the post-Soviet lecturers I once listened to. I try to give lectures with passion — as if I were on a theatrical stage — so a lecture is something that sparks emotion and curiosity. However, I do not want teaching to be my main activity. It feels like becoming the geography teacher who has never left their village. I am moving toward teaching as an art, as a craft, as a creative outlet, and simply as a way to do something good for the living world.
The world around endlessly fascinates me — especially how abstract ideas that live in our minds take shape and actually work in reality. I take great pleasure in the history of science and philosophy: the aesthetic thrill of watching centuries of thought lead to where things stand today. This site is a small place to collect such things — notes on what inspires me — and to share my teaching materials with anyone interested.
Pale Blue Dot admirer.
Professional Interests
- Fast matrix computations: methods and low-level code
- Tensor methods for Machine Learning
- ML for Signal Processing and Communications
- Applied Statistics
- Modern Math education technologies
