Alexander Rogachev
- Doctoral Student, Lecturer:Faculty of Computer Science / Big Data and Information Retrieval School
- Research Assistant:Faculty of Computer Science / AI and Digital Science Institute / Laboratory of Methods for Big Data Analysis
- Alexander Rogachev has been at HSE University since 2020.
Awards and Accomplishments
Winner of the HSE University Best Russian Research Paper Competition – 2024
Postgraduate Studies
4th year of study
Approved topic of thesis: Generative models for high energy physics experiments
Academic Supervisor: Ratnikov, Fedor
Courses (2023/2024)
- Applied Data Analysis Problems (Minor; Faculty of Computer Science; 3, 4 module)Rus
- Introduction to Deep Learning (Minor; Faculty of Computer Science; 1, 2 module)Rus
- Neural Networks and Deep Learning (Master’s programme; HSE Tikhonov Moscow Institute of Electronics and Mathematics (MIEM HSE); 1 year, 3, 4 module)Rus
- Past Courses
Courses (2022/2023)
- Machine Learning and Data Mining (Master’s programme; Faculty of Computer Science; 2 year, 1, 2 module)Eng
- Machine Learning and Data Mining (Master’s programme; Faculty of Computer Science; 1 year, 1, 2 module)Eng
- Machine Learning and Data Mining (Mago-Lego; 1, 2 module)Eng
- Neural Networks and Deep Learning (Master’s programme; HSE Tikhonov Moscow Institute of Electronics and Mathematics (MIEM HSE); 1 year, 3, 4 module)Rus
Courses (2021/2022)
- Machine Learning and Data Mining (Master’s programme; Faculty of Computer Science; 2 year, 1, 2 module)Eng
- Machine Learning and Data Mining (Master’s programme; Faculty of Computer Science; 1 year, 1, 2 module)Eng
Publications7
- Article Rogachev A., Ratnikov F. Controlling Quality for a Physics-Driven Generative Models and Auxiliary Regression Approach // EPJ Web of Conferences. 2024. Vol. 295. Article 09007. doi
- Article Rogachev A., Ratnikov F. Soft Margin Spectral Normalization for GANs // Computing and Software for Big Science. 2024. Vol. 8. No. 1. Article 12. doi
- Article Ratnikov F., Rogachev A., Mokhnenko S., Maevskiy A., Derkach D., Davis A., Kazeev N., Anderlini L., Barbetti M., Gianluca Siddi B. A full detector description using neural network driven simulation // Nuclear Instruments and Methods in Physics Research, Section A: Accelerators, Spectrometers, Detectors and Associated Equipment. 2023. Vol. 1046. Article 167591. doi
- Article Rogachev A., Ratnikov F. GAN with an auxiliary regressor for the fast simulation of the electromagnetic calorimeter response // Journal of Physics: Conference Series. 2023. Vol. 2438. Article 012086. doi
- Article Егоров Е. А., Рогачев А. И. ИССЛЕДОВАНИЕ ВЛИЯНИЯ АДАПТИВНОЙ СПЕКТРАЛЬНОЙ НОРМАЛИЗАЦИИ НА КАЧЕСТВО ГЕНЕРАТИВНЫХ МОДЕЛЕЙ И СТАБИЛЬНОСТЬ ИХ ОБУЧЕНИЯ // Доклады Российской академии наук. Математика, информатика, процессы управления (ранее - Доклады Академии Наук. Математика). 2023. Т. 514. № 2. С. 49-59. doi
- Article Золотенкова Г. В., Рогачев А. И., Пиголкин Ю. И., Эделев И. С., Борщевская В. Н., Cameriere R. Классификация возраста в судебной медицине с использованием методов машинного обучения // Современные технологии в медицине. 2022. Т. 14. № 1. С. 15-24. doi
- Chapter Ratnikov F., Rogachev A. Fast simulation of the electromagnetic calorimeter response using Self-Attention Generative Adversarial Networks, in: EPJ Web of Conferences Vol. 251: 25th International Conference on Computing in High Energy and Nuclear Physics (CHEP 2021). EDP Sciences, 2021. Ch. 03043. doi
Employment history
2019 - Research Engineer, Center for Information Technologies in Design of the Russian Academy of Sciences
2021-2022 - ML-engineer, VK
2022 - Senior Computer Vision Researcher, VK
HSE University Students Win in the AIJ Science Competition at AI Journey 2023
The International Sber Conference of Artificial Intelligence, ‘AI Journey 2023’ recently took place in Moscow. Alexander Rogachev, doctoral student of the HSE Faculty of Computer Science, and Egor Egorov, an HSE 4th-year undergraduate student became the winners of the AIJ Science competition for scientific articles on artificial intelligence that was held as part of the event. The research was carried out under the umbrella of the HSE's Laboratory of Methods for Big Data Analysis (LAMBDA).