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Oleg Gorodnitskii

Research Intern
Center for Energy Systems

Professor: Yury Maximov

Oleg graduated with honor from Moscow Institute of Physics and Technology (MIPT), Department of Control and Applied Math. During his undergraduate studies, Oleg won several awards in sport programming competitions (ACM ICPC, Moscow festival of sport programming, etc.) and was a speaker at conferences related to Machine Learning, including Information Technology and Systems 2016, Eights Traditional school “Control, Information, Optimization”, etc. Oleg finished several technical courses held in Skoltech and MIPT (Algorithms for experts, Graphical Models, etc.).

In 2016, Oleg worked on a new method for tensor completion (<<Neural Network Matrix Factorization>>) realated to Deep Learning. In 2017 Oleg worked on a new recommender system capable of simultaneous pairwise ranking and representation learning. Oleg’s areas of research interest are Deep Learning, Machine Learning and Energy Systems. He is currently working on the Power Flow Feasibility Areas problem with Konstantin Turitsyn, Yury Maximov and Anatoly Dymarsky and Recommender Systems problem with prof. Massih-Reza Amini.

Structural Modelling and Optimization for Energy Systems

Gorodnitskii Oleg, Trofimov Mikhail. Nonlinear adaptive method of matrix completion on partial observations. Articles of the 40th conference of the school ITaS 2016, 09/26/2016​.
Mikhail TrofimovSumit SidanaOleh HorodnitskiiCharlotte LaclauYury MaximovMassih-Reza Amini, Representation Learning and Pairwise Ranking for Implicit and Explicit Feedback in Recommendation Systems, 2017

B.Sc with honor: MIPT, Department of Control and Applied Mathematics.