Nikita Morozov
- Lecturer: Centre for Training Top AI Professionals
- 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
HSE University
HSE University
Awards and Accomplishments
- Young Faculty Support Programme (Group of Young Academic Professionals)

Category "New Researchers" (2024–2025)
Postgraduate Studies
Approved topic of thesis: Improving Generative Flow Networks through Reinforcement Learning
Academic Supervisor: Dmitry Vetrov
Courses (2026/2027)
- Machine Learning 1 (Bachelor’s programme; Faculty of Computer Science field of study Applied Mathematics and Information Science; 2 year, 1, 2 module)Rus
- Past Courses
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 (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
Courses (2024/2025)
- 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 (Mago-Lego; 1, 2 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; 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
Scientific Expedition to Hainan: HSE Scientists Organise Conference on Statistical AI in China
The Statistical AI Conference was held in Sanya, Hainan Island, China, from 24 to 28 August 2026. The international event brought together leading experts in statistics, machine learning, and applied AI. Alexey Naumov, Director of the AI and Digital Science Institute at the HSE Faculty of Computer Science, and Sergey Samsonov, Head of the International Laboratory of Stochastic Algorithms and High-Dimensional Inference, were among the conference organisers.
Speed, Precision, and Self-Correction: HSE Faculty of Computer Science Researchers at ICML-2026
Researchers from the HSE Faculty of Computer Science (FCS) presented their work at theInternational Conference on Machine Learning (ICML 2026) in Seoul, South Korea, one of the leading scientific events in the field. Several projects by the faculty’s researchers received the prestigious Spotlight distinction.
HSE University Presents Research Results at AI Conference in Oman
In April 2026, the International Conference on Intelligent Systems and Artificial Intelligence Applications (ISAA 2026) was held at the University of Nizwa in the Sultanate of Oman. The event was co-organised by HSE University, the University of Nizwa, and the University of Technology and Applied Sciences–Ibri. Researchers from HSE University were among the key speakers at the conference.
Technological Breakthrough: Research by AI and Digital Science Institute Recognised at AI Journey 2025
Researchers from the AI and Digital Science Institute (part of the HSE Faculty of Computer Science) presented cutting-edge AI studies, noted for their scientific novelty and practical relevance, at the AI Journey 2025 International Conference. A research project by Maxim Rakhuba, Head of the Laboratory for Matrix and Tensor Methods in Machine Learning, received the AI Leaders 2025 award. Aibek Alanov, Head of the Centre of Deep Learning and Bayesian Methods, was among the finalists.
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.