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Intake every 3 weeks! There is no "application deadline" — you can start any upcoming module!Intake every 3 weeks! — apply anytime!
Studies
Admissions
The Institute
Resources
Intake every 3 weeks! There is no "application deadline" — you can start any upcoming module!Intake every 3 weeks! — apply anytime!
Studies
Admissions
The Institute
Resources
Michael Diskin
Data Science

Michael Diskin

Lead LLM Research Engineer at Wildberries

Faculty Profile

Michael Diskin's academic and professional journey in AI and machine learning began with a BSc in Computer Science from HSE University, followed by master-level courses at the Yandex School for Data Analysis. At Wildberries, he leads the LLM R&D team, emphasising distributed training of large language models, marked by his significant contributions to NeurIPS and ICML.

His career spans roles from AI research at Rask.AI and Yandex Research, to technological innovations at Huawei and software engineering at Yandex. Michael has authored influential publications, engaged in high-level machine learning competitions, and demonstrated his commitment to education through teaching and mentoring roles at Coursera, HSE University, and YSDA.

Specialising in deep learning, reinforcement learning, and natural language processing, his skills encompass a wide array of programming languages and technologies. Michael’s keen interest in fostering advancements in AI through both theoretical research and practical applications.

Experience

  • Jan 2024 - Present

    Lead LLM Research Engineer

    Wildberries

  • Dec 2022 - Dec 2023

    Senior Research Engineer

    Rask AI

  • Feb 2021 — Dec 2022

    Research Scientist

    Yandex Research

  • Sep 2020 — Feb 2021

    Research Engineer

    Huawei

  • Dec 2017 — May 2018

    Software Engineering Intern

    Yandex

  • Jul 2017 — Sep 2017

    Research Intern

    SPbSU Center for Algorithmic Biotechnology

Education

  • Sep 2019 —May 2022

    Master-level courses in Machine Learning

    Yandex School for Data Analysis

  • Sep 2015 — Jun 2020

    BSc in Computer Science

    HSE University

Publications

  • 2021

    Distributed deep learning in open collaborations

    NeurIPS

  • 2021

    Training Transformers Together

    NeurIPS Demo

  • 2022

    Secure distributed training at scale

    ICML

  • 2022

    Distributed methods with compressed communication for solving variational inequalities, with theoretical guarantees

    NeurIPS

  • 2023

    A critical look at the evaluation of GNNs under heterophily: are we really making progress?

    ICLR

Courses by Michael

Data Science

Deep Learning in Applications (upcoming)

27 May - 14 June 2024

Bangkok

Data Science

Deep Learning in Applications (2023)

08 Apr - 26 Apr 2024

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