Alexey Davydov
Data Science

Alexey Davydov

Current position
Researcher at Steklov Math Institute
Skills
Model Theory
Algorithms
Machine Learning
Graph Theory
Discrete Mathematics

ABOUT

Alexey Davydov is a computer scientist experienced with algorithm design and machine learning. He received his bachelor degree in physics at Moscow Institute of Physics and Technology and his master degree at St. Petersburg Academic University. His main research interests are developing of competitive scheduling algorithms and usage of synthetic data in deep learning.

He has been teaching at St. Petersburg Academic University, Computer Science Center and St. Petersburg State University since 2012. Alex Davydov currently is a researcher at Steklov Math Institute where he works on theoretical research and at Neuromation where he can apply it to practice.

EXPERIENCE

Researcher
Neuromaton Inc.
2018 – Present

Junior Researcher
St. Petersburg Department of Steklov Mathematical Institute
2017 – Present

Teaching Assistant
St. Petersburg State University
2015 — 2016

EDUCATION

St. Petersburg Academical University
Ph.D. Student
2012–2017

St. Petersburg Academical University
Master Degree
2010–2012

Moscow Institute of Physics and Technology
Bachelor Degree
2006–2010

HONORS & AWARDS

  • Second Place in Intel Accelerate Contest
    Intel
    2012

  • Sponsorship Award for Research in Cryptography
    Yandex
    2011

SELECTED PUBLICATIONS

  • Land Cover Classification with Superpixels and Jaccard Index Post-Optimization
    CVPR, Conference Paper
    2018

  • Land Cover Classification from Satellite Imagery with U-Net and Lovász-Softmax Loss
    CVPR, Conference Paper
    2018

  • Building Detection from Satellite Imagery Using a Composite Loss Function
    CVPR, Conference Paper
    2018

  • Personal Insights on Three Research Directions in Networked Systems
    Conference Paper, COMSNET
    2018

  • Priority Queueing for Packets with Two Characteristics
    IEEE/ACM Transactions on Networking
    2018

  • Throughput Optimization with Latency Constraints
    Conference Paper, IEEE INFOCOM
    2017

  • Planning in Compute-aggregate Problems as Optimization Problems on Graphs
    Conference Paper, IEEE 25th ICNP
    2017

  • Bounds on the Number of Connected Components for Tropical Prevarieties
    Discrete and Computational Geometry, Volume 57, Issue 2, pp 470-493
    2017

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