Denis Kuznedelev

Denis Kuznedelev (born 12 July 1997 in Zagreb, Republic of Croatia) is a computer scientist and a Ph.D. student at Skolkovo Institute of Science and Technology. His current research involves compression and acceleration of deep neural networks and study of the efficiency of equivariant neural network architectures in problems with symmetry. He completed his undergraduate studies at MIPT University (BSc, 2019) and received Master’s degree in Physics and Applied Mathematics (MSc, 2021) from Skolkovo Institute of Science and Technology. At the moment, Denis is doing Ph.D. thesis under the supervision of Dmitriy Yarotsky and participates in the joint research project with IST on neural network compression (Klosterneuburg, Austria).

Graduated from: Skoltech/Moscow Institute of Physics and Technology

Research interests: Equivariant Neural Networks, Computer Vision

Thesis title: Investigation of equivariant neural networks efficiency

Publications

Influence of relativistic rotation on the confinement-deconfinement transition in gluodynamics

V.V. Braguta, A.Y. Kotov, D.D. Kuznedelev, A.A. Roenko

Phys. Rev. D 103, 094515  (2021) 

DOI: https://journals.aps.org/prd/abstract/10.1103/PhysRevD.103.094515

Lattice Study of QCD Properties under Extreme Conditions: Temperature, Density, Rotation and Magnetic Field

N.Y. Astrakhantsev, V.V. Braguta, N.V Kolomoyets,  A.Y. Kotov, D.D. Kuznedelev, A.A. Roenko, A.A Nikolaev

Phys. Part. Nucl. 52 4, 536-541 (2021) 

DOI: https://inspirehep.net/literature/1916821