CV
Education
- PhD (Computer Science): Constructor University, Bremen, Germany, 2024-2026 (expected)
- MSc (Math of Machine Learning): HSE University, Moscow, Russia, 2021-2023
Thesis title: Ensembling Neural Networks in the Transfer Learning Setup - BSc (Applied Mathematics & Informatics): HSE University, Moscow, Russia, 2017-2021
Thesis title: Empirical Analysis of Self-Supervised Training Properties
Languages: Russian (native), English (C1)
Work experience
- Centre of Deep Learning and Bayesian Methods — HSE University, Moscow, Russia, 2021-2023
Research assistant: Fundamental research in deep learning - SmartDec — Moscow, Russia, 2019-2020
Intern, development & analytics: Industrial research in cryptography and zero-knowledge proofs
Skills
- Programming languages:
- Proficient: Python, LaTeX
- Intermediate: C/C++, Rust
- Technologies:
- Data science: PyTorch, NumPy, Pandas, scikit-learn, matplotlib
- Linux: bash, git, ssh, docker
Publications
Talks
To Stay or Not to Stay in the Pre-train Basin: Insights on Ensembling in Transfer Learning
Paper presentation at Fall into ML 2023: Conference on Machine Learning at HSE University, Moscow, Russia
Self-supervised Pre-training with Masked Image Modeling
Research seminar at Bayesgroup, online
On the Memorization Properties of Contrastive Learning
Poster session at Workshop on Overparameterization: Pitfalls & Opportunities at ICML, online