Radoslav Neychev
Data Science

Radoslav Neychev

Current position
Ph.D. student at Moscow Institute of Physics and Technology, Senior Quantitative Analysis Officer at Raiffeisen Bank, Russia, Machine Learning Instructor at BigData Team
Skills
Deep Learning
Programming
Data Processing
System & Virtualisation

Social

ABOUT

Radoslav Neychev is a data scientist with focus on Deep Learning and Reinforcement Learning techniques. He has worked on variety of research (CERN LHCb, MIPT Machine Intelligence Lab, CC RAS) and industrial projects (Yandex, RaiffeisenBank) in different domains vary from particle identification problem to fraudulent transactions detection.

Radoslav graduated from Moscow Institute of Physics and Technology, majoring in Applied Mathematics and Machine Learning. Radoslav is reading lectures and organising practical classes at Russian top-tier universities, tech companies and summer schools.

EXPERIENCE

Head of Machine Learning Course
MIPT
Jan 2019 – Present | Moscow, Russia

Senior Quantitative Analysis Officer
Raiffeisen Bank Russia
Oct 2018 – Present | Moscow, Russia

Machine Learning Instructor
BigDataTeam
Jun 2018 – Present | Moscow, Russia

Computer Science Teaching Assistant
Moscow Institute of Physics and Technology
Sep 2017 – Present | Moscow, Russia

Research Scientist
Laboratory of Machine Intelligence, MIPT
Nov 2017 – Oct 2018 | Moscow, Russia

Senior Data Scientist
Cognive
Apr 2018 – Jul 2018 | Moscow, Russia

Research Engineer
Yandex
Jun 2016 – Apr 2018 | Moscow, Russia

Research Engineer
CERN
Jun 2016 – Apr 2018 | Geneva, Switzerland

EDUCATION

Moscow Institute of Physics and Technology
Ph.D. in Computer Science
Aug 2018 – Present

Yandex School of Data Analysis
Master's Degree in Machine Learning, Data Analysis, AI
2016–2018

Moscow Institute of Physics and Technology
Master's Degree in Computer Science
2016–2018

HONORS & AWARDS

  • Winner of the 58th MIPT Scientific Conference
    Moscow Institute of Physics and Technology
    2015

  • State Academic Scholarship for Special Achievements in Studies
    2015-2018

  • Charitable Foundation for the Development of Innovation Education Scholarship
    2014

SELECTED PUBLICATIONS

  • Machine-Learning-Based Global Particle Identification Algorithms at the LHCb Experiment
    Journal of Physics: Conference Series
    2018

  • Multicriterial LHCb Streams Optimization
    9th Computing Workshop at CERN
    2017

  • LHCb Trigger Streams Optimization
    Journal of Physics: Conference Series
    2017

  • Robust Selection of Multicollinear Features in Forecasting
    Industrial Laboratory. Diagnostics of Materials, Vol.82, N.3
    2016

  • Multimodel Forecasting of Multiscale Time Series in Internet of Things
    In Proceedings of 11th International Conference on Intelligent Data Processing: Theory and Applications
    2016

  • Constructing Robust Forecasting Model in Case of Multicollinear Features
    In Proceedings of 58th MIPT Scientific Conference
    2015

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