Evgeny Burnaev, Ph.D. Associate Professor of Center for Computational and Data-Intensive Science and Engineering (CDISE) at Skolkovo Institute of Science and Technology (Skoltech). Evgeny graduated from the Moscow Institute of Physics and Technology in 2006. After getting a Candidate of Sciences degree from the Institute for Information Transmission Problem in 2008, he stayed with the Institute as a head of the Data Analysis and Predictive Modeling Lab.

Since 2007 Evgeny carried out a number of successful industrial projects with Airbus, SAFT, IHI, and Sahara Force India Formula 1 team among others. The corresponding data analysis algorithms, developed by Evgeny and his scientific group, formed a core of the algorithmic software library for metamodeling and optimization. Thanks to the developed functionality, engineers can construct fast mathematical approximations to long-running computer codes (realizing physical models) based on available data and perform design space exploration for trade-off studies. The software library passed the final Technology Readiness Level certification in Airbus. According to Airbus experts, the application of the library “provides the reduction of up to 10% of lead time and cost in several areas of the aircraft design process”. Nowadays a spin-off company Datadvance develops a Software platform for Design Space Exploration with GUI based on this algorithmic core.

Evgeny’s current research focuses on the development of new algorithms in machine learning and artificial intelligence such as deep networks for an approximation of physical models, generative modeling, and manifold learning, with applications to computer vision and 3D reconstruction, neurovisualization. The results are published in top computer science conferences (ICML, ICLR, NeurIPS, CVPR, ICCV, and ECCV) and journals.

Evgeny Burnaev was honored with several awards for his research, including the Moscow Government Prize for Young Scientists in the category for the Transmission, Storage, Processing and Protection of Information for leading the project “The development of methods for predictive analytics for processing industrial, biomedical and financial data”, Geometry Processing Dataset Award for the work “ABC Dataset: A Big CAD Model Dataset For Geometric Deep Learning”, Symposium on Geometry Processing (2019), the Best Paper Award for the research in eSports at the IEEE Internet of People conference (2019), the Ilya Segalovich Yandex Science Prize “The best research director of postgraduate students in the field of computer sciences” (2020), the Best Paper Award for the research on modeling of point clouds and predicting properties of 3D shapes at the Int. Workshop on Artificial Neural Networks in Pattern Recognition (ANNPR) (2020).

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