Цель конкурса молодых ученых: привлечение в МГУ имени М.В. Ломоносова молодых и талантливых ученых, проводящих фундаментальные и прикладные исследования в области искусственного интеллекта, когнитивных систем и мозга.
Experimental modeling and investigation of the principles of rapid classification learning in biological intelligence systems
Scientific supervisor
Konstantin V. Anokhin
David D. Zaslavsky
Postgraduate student, Faculty of Mechanics and Mathematics, MSU
Study
Semantic analysis of texts using machine learning methods
Scientific supervisor
Valery A. Vasenin
Arseniy O. Zinkevich
Postgraduate student at the Faculty of Bioengineering and Bioinformatics of MSU
Study
Creation of an integrative neural network model for modeling the motives of binding transcription factors
Scientific supervisor
Andrey A. Mironov
Ivan S. Lazukhin
Postgraduate student at the Faculty of Computational Mathematics and Cybernetics of MSU
Study
Development of methods for forecasting and optimizing oil refining production processes based on artificial intelligence methods
Scientific supervisor
Michail I. Petrovsky
Azamat R. Mzokov
Postgraduate student at the Faculty of Economics of MSU
Study
Development of effective strategies for the development and commercialization of innovative projects in the field of artificial intelligence using the example of intelligent decision support systems (ISPS)
Scientific supervisor
Larisa V. Lapidus
Xenia I. Morozova
Postgraduate student, Faculty of Biology, MSU
Study
Determination of the boundaries and type of glioma and precancerous region by the redox state of mitochondria and the protein-lipid composition of cell cytoplasm using RAMAN spectroscopy and artificial intelligence methods
Scientific supervisor
Nadezda A. Brazhe
Xenia A. Studenikina
Postgraduate student at the Faculty of Philology of MSU
Study
Automatic modeling of matching rules
Scientific supervisor
Ekaterina A. Lutikova
Xenia Y. Shutova
Postgraduate student at the Faculty of Computational Mathematics and Cybernetics of MSU
Study
Tasks of managing a group of mobile robots
Scientific supervisor
Vasily V. Fomichev
Vsevolod O. Schegolev
Postgraduate student at the Faculty of Chemistry of MSU
Study
Using deep neural networks to predict the physico-chemical properties of antitrypanosomal drugs
Scientific supervisor
Elena V. Kudryashova
Julia I. Yarynicheva
Postgraduate student at the Geographical Faculty of MSU
Study
Artificial intelligence for the analysis and forecast of intense precipitation in the Moscow region
Scientific supervisor
Viktor M. Stepanenko
Postdocs
Daria M. Bogatova (Alexutina)
Candidate of Geological and Mineralogical Sciences, Senior Researcher at the Research Laboratory of Geoecology of the North, Faculty of Geography, MSU
Study
Development of approaches to forecasting the dynamics of the shores of the Kara Sea using machine learning methods
Scientific supervisor
Stanislav A. Ogorodov
Anne V. Dyakova
Candidate of Biological Sciences, Junior Researcher at the Department of Entomology, Faculty of Biology, MSU
Study
Multimodal antenna sensor system of miniature insects as a basis for artificial intelligence
Scientific supervisor
Alexey A. Polilov
Mary A. Kazachuk
Candidate of Physico-Mathematical Sciences, Associate Professor, Department of Intelligent Information Technologies, Faculty of Mechanical Engineering, MSU
Study
Research and development of methods for ensuring the security of computers and mobile devices based on the analysis of user behavioral biometrics data
Scientific supervisor
Машечкин Игорь Валерьевич
Anastasia A. Smirnova
Candidate of Chemical Sciences, Laboratory Assistant at the Department of Radiochemistry, Research Institute of Dosimetry and Environmental Radioactivity, Faculty of Chemistry, MSU
Study
Vulnerability detection and determination of the limits of applicability of in silico models of drug compound design using competitive machine learning
Scientific supervisor
Artem A. Mitrofanov
Michail M. Tikhomirov
Candidate of Physico-Mathematical Sciences, programmer of the 1st category of the Scientific Research Center of MSU
Study
Automatic methods for adapting multilingual resources and models to a specific domain (language, subject area)
