Optimization Methods Course Receives an Update

Irina Farisovna Yumanova, a senior researcher at the Power Engineering Digital Twins Laboratory and Associate Professor in Information Technology and Control Systems, was among the recipients of support for master's educators through the Vladimir Potanin Foundation's Scholarship Programme in the 2024/25 academic year.

She will redesign the Optimization Methods course delivered in the Artificial Intelligence in Power Engineering master's programme. The update will focus on modern methods used in machine learning, including accelerating convergence and improving the stability of gradient-based techniques, alongside adapted problems supplied by industry partners.

The course will be delivered online in Russian and is intended for students of Artificial Intelligence in Power Engineering and Energy for Smart Cities, in the degree fields of Electric Power Engineering and Electrical Engineering and Applied Mathematics.