Nikita Morozov
- Junior Research Fellow: Faculty of Computer Science / AI and Digital Science Institute / Centre of Deep Learning and Bayesian Methods
- Lecturer, Doctoral Student: Faculty of Computer Science / Big Data and Information Retrieval School
- Nikita Morozov has been at HSE University since 2021.
Education
2024
Master'sHSE University
2022
Bachelor's in Applied Mathematics and InformaticsHSE University
Awards and Accomplishments
- Young Faculty Support Programme (Group of Young Academic Professionals)
Category "New Researchers" (2024–2025)
Postgraduate Studies
1st year of study
Approved topic of thesis: Improving Generative Flow Networks through Reinforcement Learning
Academic Supervisor: Dmitry Vetrov
Approved topic of thesis: Improving Generative Flow Networks through Reinforcement Learning
Academic Supervisor: Dmitry Vetrov
Courses (2025/2026)
- Machine Learning 1 (Bachelor’s programme; Faculty of Computer Science field of study Applied Mathematics and Information Science; 3 year, 1, 2 module)Rus
- Machine Learning 1 (Bachelor’s programme; Faculty of Computer Science field of study Applied Mathematics and Information Science, Psychology, Public Administration, Sociology, Political Science; 3 year, 1, 2 module)Rus
- Machine Learning 1 (Bachelor’s programme; Faculty of Computer Science field of study Applied Mathematics and Information Science, Economics; 3 year, 1, 2 module)Rus
- Machine Learning 1 (Optional course (faculty); Faculty of Computer Science; 1, 2 module)Rus
- Machine Learning 1 (Bachelor’s programme; Faculty of Computer Science field of study Applied Mathematics and Information Science; 2 year, 1, 2 module)Rus
- Machine Learning 1 (Mago-Lego; Faculty of Computer Science)Rus
- Machine Learning 2 (Bachelor’s programme; Faculty of Computer Science field of study Applied Mathematics and Information Science; 3 year, 3, 4 module)Rus
- Machine Learning 2 (Bachelor’s programme; Faculty of Computer Science field of study Applied Mathematics and Information Science; 3 year, 3, 4 module)Rus
- Machine Learning 2 (Bachelor’s programme; Faculty of Computer Science field of study Applied Mathematics and Information Science, Psychology, Public Administration, Sociology, Political Science; 3 year, 3, 4 module)Rus
- Past Courses
Courses (2024/2025)
- Machine Learning 1 (Bachelor’s programme; Faculty of Economic Sciences field of study Applied Mathematics and Information Science, Economics; 3 year, 1, 2 module)Rus
- Machine Learning 1 (Bachelor’s programme; Faculty of Computer Science field of study Applied Mathematics and Information Science; 3 year, 1, 2 module)Rus
- Machine Learning 1 (Bachelor’s programme; Faculty of Social Sciences field of study Applied Mathematics and Information Science, Psychology, Public Administration, Sociology, Political Science; 3 year, 1, 2 module)Rus
- Machine Learning 1 (Mago-Lego; 1, 2 module)Rus
- Machine Learning 1 (Bachelor field of study Economics; 3 year, 1, 2 module)Rus
- Machine Learning 2 (Bachelor’s programme; Faculty of Economic Sciences field of study Applied Mathematics and Information Science, Economics; 3 year, 3, 4 module)Rus
- Machine Learning 2 (Bachelor’s programme; Faculty of Computer Science field of study Applied Mathematics and Information Science; 3 year, 3, 4 module)Rus
- Machine Learning 2 (Bachelor’s programme; Faculty of Social Sciences field of study Applied Mathematics and Information Science, Psychology, Public Administration, Sociology, Political Science; 3 year, 3, 4 module)Rus
- Machine Learning 2 (Bachelor’s programme; Faculty of Computer Science field of study Applied Mathematics and Information Science; 3 year, 3, 4 module)Rus
- Probability Theory (Bachelor’s programme; Faculty of Computer Science field of study Applied Mathematics and Information Science; 2 year, 1-3 module)Rus
Courses (2023/2024)
- Deep Learning 1 (Bachelor’s programme; Faculty of Computer Science field of study Applied Mathematics and Information Science; 3 year, 2, 3 module)Eng
- Machine Learning 1 (Bachelor’s programme; Faculty of Economic Sciences field of study Economics; 3 year, 1, 2 module)Rus
- Machine Learning 1 (Bachelor’s programme; Faculty of Computer Science field of study Applied Mathematics and Information Science, field of study Applied Mathematics and Information Science; 3 year, 1, 2 module)Rus
- Machine Learning 2 (Bachelor’s programme; Faculty of Computer Science field of study Applied Mathematics and Information Science, field of study Applied Mathematics and Information Science, field of study Applied Mathematics and Information Science; 3 year, 3, 4 module)Rus
Courses (2022/2023)
- Introduction to Deep Learning (Bachelor’s programme; Faculty of Computer Science field of study Applied Mathematics and Information Science; 3 year, 1-3 module)Eng
- Machine Learning 1 (Bachelor’s programme; Faculty of Economic Sciences field of study Economics; 3 year, 1, 2 module)Rus
- Machine Learning 1 (Bachelor’s programme; Faculty of Computer Science field of study Applied Mathematics and Information Science; 3 year, 1, 2 module)Rus
- Machine Learning 2 (Bachelor’s programme; Faculty of Computer Science field of study Applied Mathematics and Information Science, field of study Applied Mathematics and Information Science; 3 year, 3, 4 module)Rus
13
Nov
2025
HSE Scientists Optimise Training of Generative Flow Networks
Researchers at the HSE Faculty of Computer Science have optimised the training method for generative flow neural networks to handle unstructured tasks, which could make the search for new drugs more efficient. The results of their work were presented at ICLR 2025, one of the world’s leading conferences on machine learning. The paper is available at Arxiv.org.