Recent Posts

Hello everyone, On Tuesday, $3^{\text{rd}}$ November my Ph.D. defence took place. Title: Proximal Optimization with Automatic Dimension …

Title: Proximal Gradient Methods with Adaptive Subspace Samplings Together with Gilles Bareilles, Yassine Laguel, Franck Iutzeler, and …

Hello everyone, On Tuesday, $29^{\text{th}}$ September I will make a rehearsal for my Ph.D. defence. Title: Proximal Optimization with …

Title: Adaptive Catalyst for smooth convex optimization Together with Anastasiya Ivanova, Egor Shulgin, and Alexander Gasnikov from …

Recent & Upcoming Talks

Many applications in machine learning or signal processing involve nonsmooth optimization problems. This nonsmoothness brings a …

In this talk, we present an asynchronous distributed learning algorithm where parameter updates are performed by worker machines …

In this talk, we present a first-order optimization algorithm for distributed learning problems. We propose an efficient sparsification …

Many machine learning and signal processing applications involve high-dimensional nonsmooth optimization problems. The nonsmoothness is …

We present an asynchronous optimization algorithm for distributed learning, that efficiently reduces the communications between a …

Recent Publications

In this paper, we propose an asynchronous distributed learning algorithm where parameter updates are performed by worker machines …

Progressive Hedging is a popular decomposition algorithm for solving multi-stage stochastic optimization problems. A computational …

Many applications in machine learning or signal processing involve nonsmooth optimization problems. This nonsmoothness brings a …

In this paper, we present the generic framework that allows accelerating almost arbitrary non-accelerated deterministic and randomized …

In this paper, we present an asynchronous optimization algorithm for distributed learning, that efficiently reduces the communications …

Teaching

Optimisation Numérique

Basic course on numerical optimization (theory and implementation)

Refresher course$:$ Numerical Matrix Analysis and Optimization

This short course focuses on matrix analysis and optimization

Optimisation Numérique

Basic course on numerical optimization (theory and implementation)

Convex and Distributed Optimization

Incremental and Stochastic Optimization for Learning, Spark, Distributed Optimization.

Refresher course$:$ Numerical Matrix Analysis and Optimization

This short course focuses on matrix analysis and optimization

Experience

 
 
 
 
 

Senior Software Developer

Yandex

Nov 2021 – Present Moscow, Russia
Working on the drivers’ positioning. Adjusting raw GPS signals to road-graph. Predicting future positions. Developing quality metrics.
 
 
 
 
 

Senior Software Developer (team lead)

Huawei

Feb 2021 – Nov 2021 Moscow, Russia
Leading C++ developing tem working on PCB router.
 
 
 
 
 

Senior Software Developer

Huawei (as contractor)

Aug 2020 – Feb 2021 Moscow, Russia
Writing from the scratch the geometrical library on C++ for PCB router.
 
 
 
 
 

Teaching Assistant

Université Grenoble Alpes

Sep 2018 – Nov 2020 Grenoble, France

2019 - 2020

  • Matrix Analysis and Numerical Optimization

  • Numerical Optimization

2018 - 2019

  • Matrix Analysis and Numerical Optimization

  • Convex and Distributed Optimization

  • Numerical Optimization

 
 
 
 
 

Software Developer

Altium

Jan 2016 – Sep 2017 Moscow, Russia
 
 
 
 
 

Intern Decision Management Unit

Citibank

Jul 2014 – Feb 2015 Moscow, Russia
 
 
 
 
 

Teaching Assistant

Higher School of Economics

Sep 2013 – Jun 2015 Moscow, Russia
  • Calculus
 
 
 
 
 

Mathematical Olympiad Works Inspector

International Mathematical Tournament of Towns

Sep 2011 – Dec 2015 Moscow, Russia

Contact