Research interests


  • Shear flows
  • Transition to turbulence
  • Pattern formation
  • Time series forecasting
  • Predictability analysis
  • Approximate computing

Education


2017 – 2020
University of Leeds

Ph.D. in Applied Mathematics

2015 – 2016
Imperial College London

M.Sc. in Advanced Computational Methods, Distinction

2008 – 2014
Bauman Moscow State Technical University

Specialist Degree, Diploma with honours

Experience


Oct 2021 – now
Huawei Technologies Co., Ltd., Saint Petersburg Software Technology Innovation Lab

Senior Researcher / Team Lead

Time series analysis and causality analysis in the context of telecom networks:

  • Large-scale traffic forecasting for thousands of network elements (both long-term and short-term forecasting)
  • Adaptive sampling of time series data collected from network elements
  • Predictability analysis for non-stationary time series and discrete events (alarms)
Oct 2020 – Oct 2021
University of Oxford, Department of Physics

Postdoctoral Research Assistant

This is the work within the project ITHACA «An Information Theoretic Approach to Improving the Reliability of Weather and Climate Simulations» led by Prof. Tim Palmer. It was aimed at improving the computational efficiency of a large-scale meteorological model (IFS by ECMWF):

  • Computing radiative transfer with reduced numerical precision
  • Accelerating MPI communications by reducing numerical precision
  • Developing debug tools to ease the search for numerical instabilities and errors while working with low-precision arithmetics

Feb 2015 – Sep 2015
Scientific Technical Centre «ELINS»

C++ Developer

Development of an application for telemetry processing based on Qt.

Mar 2014 – Sep 2014
B&R Industrial Automation

C Developer

Development of industrial control systems.

Mar 2013 – Nov 2013
AST Group

C/C++ Developer

Development of a security-aimed platform written on C.

Sep 2011 – Feb 2013
Bauman Moscow State Technical University

C++/Python Developer

Development of a distributed CAE system written on C++ and Python.

Math Stack


Dynamical systems theory
  • Finite-amplitude instabilities
  • Stability analysis
  • Chaos theory
  • Bifurcation theory
Numerical analysis
  • Low-precision arithmetics
  • ODE/PDE solvers
  • Approximation theory
Statistics
  • Time series analysis
  • Bayesian inference
  • Additive models
Machine learning
  • Echo state networks
  • Decision trees / random forest
  • PCA / autoencoders

Technical Stack


Python
  • numpy
  • scipy
  • matplotlib
  • pandas
  • django
DS/ML libraries
  • scikit-learn
  • statsmodels
  • torch
Web
  • HTML
  • CSS/Bootstrap
  • JavaScript/Vue.js
  • Plotly
  • Django
  • Wagtail
Software development
  • Linux/Windows/cross-platform
  • git/gitlab/SVN
  • VSCode
Other
  • C/C++11/14/17
  • SQL
  • Latex