Igor Sokolov
Igor Sokolov

PhD Candidate in Applied Mathematics and Computational Science

About Me

(Website is on development)

I am a PhD candidate in Applied Mathematics and Computational Science at King Abdullah University of Science and Technology (KAUST), working under the supervision of Professor Peter RichtΓ‘rik. I also completed my MS degree at KAUST in the same research group.

Prior to KAUST, I received both my undergraduate and MS degrees in Applied Mathematics and Physics from Moscow Institute of Physics and Technology (MIPT), where I also worked as a junior researcher in the Laboratory of Advanced Combinatorics and Network Applications.

My research interests lie at the intersection of Optimization and Machine Learning, with a particular focus on Federated Learning and Communication-Efficient Distributed Algorithms. I have contributed to multiple publications at top-tier conferences including NeurIPS and ICML. Additionally, I serve as a reviewer for the TMLR journal and major machine learning conferences including NeurIPS, ICML, and ICLR.

Beyond academia, I am passionate about outdoor activities including hiking, wall and mountain climbing, alpine skiing, and traveling.

Feel free to contact me via email if you would like to discuss research, either in person or online.

Interests
  • Optimization for Machine Learning
  • Federated Learning
  • Communication-Efficient Distributed Algorithms
Education
  • PhD in Applied Mathematics and Computational Science

    King Abdullah University of Science and Technology

  • MS in Applied Mathematics and Computational Science

    King Abdullah University of Science and Technology

  • MS in Applied Mathematics and Physics

    Moscow Institute of Physics and Technology

  • BS in Applied Mathematics and Physics

    Moscow Institute of Physics and Technology

πŸ“š My Research

Use this area to speak to your mission. I’m a research scientist in the Moonshot team at DeepMind. I blog about machine learning, deep learning, and moonshots.

I apply a range of qualitative and quantitative methods to comprehensively investigate the role of science and technology in the economy.

Please reach out to collaborate πŸ˜ƒ

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