Education and Training
Master of Science in Machine Learning, Data Science and AI, Aalto University (09/2021 – 05/2023), Espoo, Finland.
Final grade: 5.0/5.0
Bachelor of Computer Science with minor in economics, Saint-Petersburg State University (09/2017 – 06/2021), St. Petersburg, Russia.
Final grade: 4.9/5.0
Oxford summer school in Machine Learning for Healthcare (08/2022)
Research Experience
Research Assistant in Probabilistic Machine Learning (09/2022 – 02/2024).
Developed Bayesian nonparametric methods for modeling individualized treatment-response curves from noisy, sparse time
series. Focused on deriving a multi-output Gaussian Process (GP) model using coregionalization to incorporate information across individuals and treatments. Built on Conventional GP, Latent Force (ODE-based), and Convolved GP models. Stack: Python
(GPflow), R (Stan).
Research Intern in Statistical Machine Learning (06/2022 – 09/2022).
Developed a multi-output Bayesian regression model for multi-trait phenotypic analysis with grouped genetic effects. Improved
Gibbs sampler reduced covariance estimation error and cut runtime by nearly one-third. Stack: Python, C++.
Research Assistant in Explainable Machine Learning (11/2021 – 05/2022).
Worked on Explainable Empirical Risk Minimization, developing and testing ML optimization methods that integrate user
experience as a regularizer.
Publications
Nonparametric modeling of the composite effect of multiple nutrients on blood glucose dynamics (2023).
Accepted to ML4H Symposium 2023.
PMLR, Toolkit
Explainable Empirical Risk Minimization (2022).
Accepted to Neural Computing & Applications 2023.
Springer
Honours and Awards
- Aalto Dean’s incentive-based scholarship for the Students of School of Science with excellent results (11/2023)
- Kyunghyun Cho's award for women in computer science (11/2022)
- Aalto Dean’s incentive-based scholarship for the Students of School of Science with excellent results (10/2022)
- Prize-winner of the 10th Congress of Young Scientists in the section "Machine learning and cognitive technologies" (04/2021)
- Winner of the Competition of scientific works within the 63rd All-Russian Scientific Conference of the MIPT Phystech-School of Applied Mathematics and Informatics (12/2020)
- Best oral presentation in the 63rd All-Russian Scientific Conference of the MIPT Phystech-School of Applied Mathematics and Informatics (11/2020)
Work Experience
Machine Learning Engineer, RemedyLogic (10/2023 – Current).
Developing the AI-based recommendation system, focusing on probabilistic ML and computer vision, to support the radiologists
decision-making process.
Teaching Assistant, Aalto University (11/2021 – 12/2022).
Educational materials preparation for ML courses.
Junior Data Scientist, Quantori (05/2021 – 09/2021).
Analyzed the structure of .pdf data tables for future OCR application. Reviewed and modified CascadeTabNet for potential
deployment in a healthcare-related PDF parsing project.
Machine Learning Engineer, SberTech (08/2020 – 04/2021).
Developed a statistical model to predict delivery travel costs and applied ML algorithms for trip data analysis. Used time series
techniques (ARIMA, SARIMA, ARMA, Holt-Winters) for cost forecasting.