Research and development for projects related to sensors on mobile devices, especially in image proccessing applications
Research and development for projects related to such topics as 3D modeling, deep learning, visual navigation and localization
Research and development in backup and cloud data storage systems
Research and development in EDA/ECAD systems, automatic synthesis and optimization of nano-scale topologies for integral circuit components
A visual navigation system for a drone development
Intel Advisor XE and parallel runtimes, e.g. Intel TBB and Intel OpenMP, integration
Research and development of methods to move sheet and wire bodies by vector in CAD systems
Topic: "Research and development of methods for automatic determining of geomeric constraints based on declarative programming and formal methods". The project covers such topics as model checking, boolean satisfiability, discrete optimization, EDA/CAD
Research and development of a visual navigation system for a walking robot
Research and development of visual navigation algorithms for mobile robots
deep learning, computational geometry, 3D reconstruction, SLAM, OpenCV, Open3D, ROS, Pytorch, TensorFlow
boolean satisfiability, constraint satisfaction programming, formal methods, graph theory, local search, mixed integer programming
C++17, Python, Rust, Tcl
algorithms, problem solving, scientific writing, Docker, CAD/EDA, Linux, Git, Atlassian
English (TOEFL 94 / 120)
P. Kirsanov, et al.; IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2019)
S. Bykov, N. Ryzhenko N., A. Sorokin; East-West Design & Test Symposium (EWDTS), 2016 IEEE. IEEE, 2016
N. Ryzhenko, A. Sorokin, S. Bykov, M. Talalay; Problems of Advanced Micro- and Nanoelectronic Systems Development, 2014
N. Ryzhenko, A. Sorokin, S. Bykov, M. Talalay; Problems of Advanced Micro- and Nanoelectronic Systems Development, 2014
S. Bykov, V. Zhoga, V. Skakunov, V. Shurigyn; International Scientific-and-Technological Conference "Extreme robotics", "Politehnika-service", Saint-Petersburg (in Russian)
S. Bykov, V. Leontev, V. Skakunov; VSTU News, 3, No 13, p. 18-21, 2012 (in Russian)
Microframework that trains a semantic segmentation model for BDD100K outdoor dataset. Uses Pytorch, Sacred, Albumentations
K-Means algorithm implementation using modern C++ and libeigen3
Demonstrates how to use Rust and Exonum framework for deploing private blockchain