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Applied Information Theory group
Меню
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Projects
Deep Neural Network Based Decoder Design for 5G Codes
Development of error-correcting codes for future 5G physical layer
Development of random multiple access methods for massive machine type communications
Development of short low-complexity decoded error-correcting codes for IoT
Information-Theory Based Analysis of Deep Neural Networks
Investigation of Coding Techniques for High-Loaded Distributed and Cloud Storage Systems
Theoretical fundamentals of random multiple access channels with applications to massive machine-type communications and digital fingerprinting
Unified FEC for optical lines
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Awards
Russian Government Award in Science and Technology for Young Scientists
(A. Frolov, 2016)
Huawei RRC Best Cooperation Project Award
(G. Kabatiansky, 2016)
Moscow Government Award for Young Scientists
(A. Frolov, 2013)
Russian President Scholarship
(A. Frolov, 2013; P. Rybin, 2015; S. Kruglik, 2016)
Best Teacher of the National Research University “Higher School of Economics”
(G. Kabatiansky, 2014 and 2016)