Nikita Kazeev
- Postgraduate Student:Faculty of Computer Science / Laboratory of Methods for Big Data Analysis
Young Faculty Support Program (Group of Young Academic Professionals)
Category "New Researchers" (2017-2018)
Postgraduate Studies
3rd year of study
Approved topic of thesis: Machine Learning for particle identification in the LHCb detector
Academic Supervisor: Ustyuzhanin, Andrey
Student Term / Thesis Papers
- Bachelor
D. Dubov «Learning Spacecraft Control with Reinforcement Learning». Faculty of Computer Science, 2018
- Master
L. Gremyachikh «Automation of Satellite Collision Avoidance Maneuvers with Deep Reinforcement Learning». Faculty of Computer Science, 2018
Publications10
- Article Ratnikov F., Баранов А. С., Borisyak M. A., Derkach D., Hushchyn M., Kazeev N., Ustyuzhanin A. First measurement of the CP-violating phase ϕdds in B s 0 → (K+π−)(K−π+) decays // Journal of High Energy Physics. 2018. Vol. 2018. P. 1-31. doi
- Article Derkach D., Hushchyn M., Likhomanenko T., Rogozhnikov A., Kazeev N., Chekalina V., Нейчев Р. Г., Stanislav K., Ratnikov F. Machine-Learning-based global particle-identification algorithms at the LHCb experiment // Journal of Physics: Conference Series. 2018. Vol. 1085. No. 4. P. 1-5. doi
- Article Hushchyn M., Derkach D., Ustyuzhanin A., Ratnikov F., Kazeev N., Баранов А. С., Borisyak M. A. Measurement of CP observables in B± → D(⁎)K± and B± → D(⁎)π± decays // Physics Letters. Section B: Nuclear, Elementary Particle and High-Energy Physics. 2018. Vol. 777. P. 16-30. doi (in press)
- Article Kazeev N., Derkach D., Hushchyn M., Ratnikov F., Ustyuzhanin A. Search for the rare decay Λ c+→ p μ+ μ− // Physical Review D - Particles, Fields, Gravitation and Cosmology. 2018. Vol. 97. P. 091101-1-091101-10. doi
- Article Ustyuzhanin A., Derkach D., Borisyak M. A., Баранов А. С., Hushchyn M., Kazeev N., Ratnikov F. Search for weakly decaying bb-flavored pentaquarks // Physical Review D - Particles, Fields, Gravitation and Cosmology. 2018. Vol. 97. P. 032010-1-032010-11. doi
- Article D. Derkach, N. Kazeev, R Neychev, A. Panin, Trofimov I., A. Ustyuzhanin, Vesterinen M. LHCb trigger streams optimization // Journal of Physics: Conference Series. 2017. Vol. 898. No. 6. P. 1-6. doi
- Article Hushchyn M., Ustyuzhanin A., Derkach D., Ratnikov F., Баранов А. С., Kazeev N., Borisyak M. A. Measurement of CP asymmetry in D0→ K− K+ decays // Physics Letters. Section B: Nuclear, Elementary Particle and High-Energy Physics. 2017. Vol. 767. P. 177-187. doi (in press)
- Article LHCb C., Borisyak M. A., Derkach D., N. Kazeev, Rogozhnikov A., Ratnikov F., Ustyuzhanin A. Observation of the doubly charmed baryon Ξ++cc // Physical Review Letters. 2017. Vol. 119. No. 11. P. 1-10. doi
- Article LHCb C., Derkach D., Kazeev N., Ratnikov F., Rogozhnikov A., Ustyuzhanin A. Search for Baryon-Number Violating Ξ b 0 Oscillations // Physical Review Letters. 2017. Vol. 119. No. 18. P. 181807-1-181807-9. doi
- Article Kazeev N., Ustyuzhanin A., Artemov A., Redkin A. Event Index — an LHCb Event Search System // Journal of Physics: Conference Series. 2015. Vol. 664. No. 3. P. 032019-032019. doi
Conferences
- 2018
23rd International Conference on Computing in High Energy and Nuclear Physics (CHEP-2018) (София). Presentation: Machine Learning based Global Particle Identification Algorithms at the LHCb Experiment
10th International Workshop on Ring Imaging Cherenkov Detectors (RICH 2018) (Москва). Presentation: Cherenkov Detectors Fast Simulations Using Neural Networks
IV international conference on particle physics and astrophysics (ICPPA) (Москва). Presentation: Machine learning at LHCb
- 2016
22nd International Conference on Computing in High Energy and Nuclear Physics, CHEP 2016 (San Francisco). Presentation: LHCb trigger streams optimization
4th National eScience Symposium Science in a Digital World (Amsterdam). Presentation: Reproducible Machine Learning for Humans
DevFest Siberia (Новосибирск). Presentation: Изучая Вселенную при помощи больших данных и машинного обучения
17th International workshop on Advanced Computing and Analysis Techniques in physics research (ACAT) (Valparaiso). Presentation: LHCb data processing optimization using Event Index
Inter-experimental LHC Machine Learning (IML) Working Group meeting (Geneva). Presentation: Optimisation of data storage (Clustering with gradient descent)
81st LHCb Collaboration Week (Сантьяго-де-Компостела). Presentation: HLT streaming optimization
Third Machine Learning Summer School Held in UK
On July 17-23 the Third Machine Learning summer school organized by Yandex School of Data Analysis, Laboratory of Methods for Big Data Analysis at the National Research University Higher School of Economics and Imperial College London was held in Reading, UK. 60 students, doctoral students and researchers from 18 countries and 47 universities took part in the event.
