Research team

I am the head of the Generative AI research group at Skoltech. My current group mostly consists of PhD students. I also supervise some MSc students in their research in generative modeling and optimal transport. Some of students are supervised jointly with prof. E. Burnaev.

PhD Students

  • Nikita Gushchin: Efficient methods for solving entropic optimal transport problems;
  • Milena Gazdieva: Parametric methods for computing OT mappings for imaging tasks;
  • Alexander Kolesov: Scalable Generative modeling approaches based on schrodinger bridges;
  • Petr Mokrov: Methods for solving optimal transport problems with general costs;
  • Mikhail Persiianov: Scalable methods for inverse optimal transport;
  • Igor Udovichenko: Scalable methods for optimal transport with applications to time series tasks;
  • Xavier Aramayo: Scalable methods for computing Gromov-Wasserstein Optimal Transport;
  • Sergey Kholkin: Adversarial generative modeling approaches based on schrodinger bridges;
  • Grigoriy Ksenofontov: Scalable computation methods for schrodinger bridges;
  • Alexey Leonov: Distillation method for diffusion bridges for image super-resolution tasks;

MSc Students

  • 2nd year:: David Li, Sergey Karpukhin, Sergey Kushneryuk, Roman Tarasov;
  • 1st year: Vladislav Gromadski, Arseny Egorov, Tikhon Mavrin, Irina Zabaryanskaya;

MSc Alumni

  • Sergey Kholkin (2023-24): Optimal Schrödinger Bridge Matching (Grade: A, Best thesis award);
  • Maxim Nekrashevich (2021-24): Neural Gromov-Wasserstein Optimal Transport (Grade: A);
  • Nikita Andreev (2022-24): Improving, analyzing and speeding up image-to-image translation models based on Neural Optimal Transport (Grade: A);
  • Kirill Tamogashev (2022-24): Acoustic Style Transfer with Neural Generative Models (Grade: A);
  • Xavier Aramayo (2022-24): Scalable methods for computing entropic Gromov-Wasserstein Optimal Transport (Grade: A);
  • Polina Karpikova (2022-23): Diverse Image Inpainting using Neural Optimal Transport (Grade: A);
  • Nikita Glukhov (2022-23): Optimal Transport for Semi-supervised Data Translation (Grade: A);