Fedor Aleksandrovich Buzaev is a Lecturer and Junior Research Fellow at the Faculty of Computer Science of the National Research University Higher School of Economics (HSE), where he also serves as a postgraduate student in his second year of study. He began his work at HSE in 2024 and is affiliated with both the Institute of Artificial Intelligence and Digital Sciences and the Department of Big Data and Information Retrieval. His educational background includes a Master's degree in Applied Mathematics and Computer Science from HSE (2023) and a Bachelor's degree in Electric Power Engineering and Electrical Engineering from MPEI (2020). Buzaev's research focuses on the intersection of physics and machine learning, particularly in developing physics-informed neural networks for solving complex scientific problems. His work spans several key areas including climate prediction, computational physics, and the solution of partial differential equations. He has made significant contributions to optimizing neural network architectures for scientific computing applications, with a particular emphasis on solving the nonlinear Schrödinger equation and other physics-based problems. His professional experience includes working as a deep learning researcher at Zvuk.com (since December 2024), a junior researcher at the Research and Educational Laboratory of Big Data Analysis Methods (since June 2023), and previous positions at Huawei RRI, JuniStat, and EdisonLab. He teaches the "Machine Learning 1" course at HSE and has expertise in multiple programming languages and research methodologies. Buzaev is currently working on his dissertation with the approved topic "Climate prediction using physically-informed neural networks" under the supervision of Fedor Dmitrievich Ratnikov. His research demonstrates a strong commitment to advancing the application of machine learning techniques in scientific domains, particularly where physical constraints and equations guide the learning process.


