11, Pokrovsky boulevard.
Phone: +7 (495) 531-00-00 *27254
Rodomanov A., Kropotov D.
SIAM Journal on Optimization. 2020. Vol. 30. No. 3. P. 1878-1904.
A. Boldyrev, D. Derkach, F. Ratnikov et al.
Journal of Instrumentation. 2020. Vol. 15. P. 1-7.
Dvurechensky P., Eduard Gorbunov, Gasnikov A.
European Journal of Operational Research. 2021. Vol. 290. No. 2. P. 601-621.
Kuznetsov S., Kaytoue M., Belfodil A.
In bk.: International Journal of General Systems. Iss. 49. 2020. P. 271-285.
Kaledin M., Moulines E., Naumov A. et al.
In bk.: Proceedings of Machine Learning Research. Vol. 125: Proceedings of Thirty Third Conference on Learning Theory. 2020. P. 2144-2203.
The Faculty of Computer Science was created with the goal of becoming one of the world’s leading faculties for developers and researchers in data analysis, machine learning, big data, theoretical computer science, bioinformatics, system and software engineering, system programming, and distributed computing. In cooperation with major companies like Yandex, Sberbank, SAS, Samsung, 1C, and many others, the Faculty provides both deep theoretical knowledge and hands-on practical experience in many branches of contemporary computer science.
We are proud to announce that in 2020 eight candidates of computer science defended their theses at the Faculty. There have been six candidate defences in 2019. Prior to 2018, there were only degrees of candidate and doctor of technical or physical-mathematical sciences in Russia. Degrees in computer science have become possible due to HSE University's ability to grant its own degrees.
Candidates of computer science:
Thesis: Bayesian approach in deep learning: refinement of discriminative and generative models
Academic supervisor: Dmitry Vetrov
Thesis: Development of a method for solving structural optimization problems
Academic supervisor: Alexander Gasnikov
Thesis: Neural network model for human recognition by gait indifferent types of video
Academic supervisor: Anton Konushin
Thesis: Machine Learning for particle identification in the LHCb detector
Academic supervisors: Barbara Sciascia, Andrey Ustyuzhanin, Davide Pinci
Thesis: Machine learning methods for data quality monitoring in natural sciences
Academic supervisor: Andrey Ustyuzhanin
Thesis: Methods and tools for enhancing the efficiency of process mining algorithms
Academic supervisor: Irina Lomazova
Thesis: Learning generative probabilistic models for mass spectrometry data identification
Academic supervisor: Attila Kertesz-Farkas
Thesis: Interestingness measures of closed patterns for data mining and knowledge discovery
Academic supervisor: Sergey Kuznetsov
Congratulations and best wishes to the new candidates!