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Phone:
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Address: 11 Pokrovsky Bulvar, Pokrovka Complex, room T920
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SPIN-RSCI: 2734-5363
ORCID: 0000-0002-0925-3130
ResearcherID: AAY-9604-2020
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According to Term Schedule, typically from 1200 to 1900; Mon, Tue, Thu,Fri
Supervisors
A. Naumov
E. Sokolov
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Maxim Kaledin

  • Maxim Kaledin has been at HSE University since 2015.

Responsibilities

Research in Deep Learning for sound applications.

Teaching on Applied Mathematics and Software Engineering programs (Faculty of Computer Science).

Education

  • 2019

    Master's
    HSE University

  • 2017

    Bachelor's
    HSE University

Courses (2023/2024)

Courses (2022/2023)

Courses (2021/2022)

Courses (2020/2021)

Courses (2019/2020)

Courses (2018/2019)

Numerical Methods (Bachelor’s programme; Faculty of Computer Science; 3 year, 1, 2 module)Rus

Publications3


Employment history

Research

Dec 2020 - Aug 2023   Research Fellow, HDI Lab, Higher School of Economics, main topics: stochastic optimal control, high-dimensional probability theory.

Apr 2018 - Dec 2020  Research Intern, HDI Lab, Higher School of Economics, main topics: stochastic optimal control, high-dimensional probability theory.

Jun-Aug 2018  Research Intern, Huawei Moscow Research Center, main topics: antenna modelling, FDD systems.

 

Teaching

Sept. 2023 - now Associate Professor, HSE Faculty of Computer Science.

Sept. 2022 - now Senior Lecturer, HSE Faculty of Computer Science.

2017-June 2022  Lecturer, HSE Faculty of Computer Science.

Sept-Dec 2019    Lecturer, Stochastic Calculus, OZON Masters School.

Sept-Dec 2018    Teaching Assistant, Stochastic Calculus, MS-1 course (HSE, Faculty of Computer Science, Statistical Learning Theory MS program).

Sept-Dec 2016    Teaching Assistant, Numerical Methods, third-year bachelor's course (HSE faculty of Computer Science).

Apr-Jun 2015,2016,2017  Teaching Assistant, Abstract Algebra, first-year bachelor's course (HSE Faculty of Computer Science).

Timetable for today

Full timetable

First Cohort Graduates from Master’s Programme in Statistical Learning Theory

The Master's Programme in Statistical Learning Theory was launched in 2017. It is run jointly with the Skolkovo Institute of Science and Technology (Skoltech). The programme trains future scientists to effectively carry out fundamental research and work on new challenging problems in statistical learning theory, one of the most promising fields of science. Yury Kemaev and Maxim Kaledin, from the first cohort of programme graduates, sat down with HSE News Service to talk about their studies and plans for the future.

First Cohort Graduates from Master’s Programme in Statistical Learning Theory

The Master's Programme ‘Statistical Learning Theory’ was launched in 2017, and is run jointly with the Skolkovo Institute of Science and Technology(Skoltech).