About

A mathematician by training, I am now interested in the mathematically rich areas of machine learning, conducting research that aims to benefit both theoreticians and practitioners.

My key research areas are geometric learning and uncertainty quantification. My work in these areas has won best-paper-type honors at top machine learning conferences twice.

Since spring 2025, I am a lecturer (tenured assistant professor) in machine learning at the University of Edinburgh. More specifically, I am part of the Institute for Machine Learning within the School of Informatics.

Before Edinburgh, I was a postdoc (ETH Fellow) in the Learning & Adaptive Systems Group at ETH Zürich, led by Prof. Dr. A. Krause. I received my PhD in harmonic analysis from the Steklov Mathematical Institute (St. Petersburg Department) in 2022, advised by Prof. S. V. Kislyakov. I was also co-mentored by Prof. M. A. Lifshits in Gaussian processes.

On a personal note, I am happily married to Ekaterina Noskova, a researcher in bioinformatics.

PhD and Postdoc Openings

I am always looking for PhD students and postdocs passionate about geometric learning or uncertainty quantification. Explore my research group here here. More about vacancies here.

For the 2026–2027 cycle:

• I plan to hire through the CDTs and scholarships listed on the vacancies page.
• Home fee applicants are highly encouraged due to much greater funding availability.
• Biomedical AI CDT: Please contact me as early as summer 2026 if you have a project idea.