Knowledge and skills:

• Machine Learning: PyTorch, scikit-learn.
• Python, C/C++.
• Calculus, Algebra, Numerical analysis, Probability theory and Mathematical Statistics, Algorithms and Data Structures.
• Molecular Biology and Biotechnology, Algorithms in Bioinformatics (github).
• Data Analysis: SQL, Statistical Hypothesis Testing (github).

First Education:

St. Petersburg State University, Department of Mathematics and Mechanics, Master of Astronomy, Sep, 2014 - June, 2019.

Degree Thesis:

Topic: "The Effect of Close Approach to a Planet on the Rotation of an Asteroid".
In this work I have developed a program in C++ using Boost library and numerical methods for calculating an asteroid trajectory in the Solar system. github

Second Education:

National Research University Higher School of Economics, Master of Computational Biology and Bioinformatics, Sep, 2021 - June, 2023.

Scientific work in progress:

Research Supervisor: Alexander Tyshkovsky (Harvard Medical School)

Topic: "Building of high-precision aging clocks based on gene expression data using deep learning methods and their application to search for optimal combinations
of interventions that prolong life."
I am testing Variational Autoencoder with Disentangled Representation and an additional layer for predicting age. github

Additional education and competitions:

• Bioinformatics Summer School 2019 on the topic ``Bioinformatics in Research of Aging and Biological Development'' and the project.
• 4th place in SignalNeuroHack hackathon with Huawei research project. 
• Completed the course ``Deep Learning на пальцах (Put Simply)'' by Computer Science Center and Novosibirsk State University (github). Also Reinforcement Learning tasks using DQN algorithm and Policy Gradient (github).
• Specialization ``Machine Learning and Data Analysis'' by Yandex on Coursera (github).
• Stepik courses certificates.
• The course Biology through the eyes of venture capitalists by Blastim.