Dmitry Shashev, Ph.D in Engineering

Affiliation: National Research Tomsk State University

Address: 634050, Russia, Tomsk, Lenin ave., 36/3, Tomsk State University, Faculty of Innovative Technologies

Email: [email protected]

Positions:

• Assistant professor (from 2018),
• Head of the High-Performance Reconfigurable Systems Laboratory (from 2018),
• Deputy Dean for R&D at the Faculty of Innovative Technologies (from 2019)

Field of interest:

• Image processing and recognition;
• Machine learning;
• Autonomous vehicles;
• Robotics

Subjects taught:

• Artificial Intelligence and Machine Learning;
• Technological process automation;
• Metrology

Finished his studies in Tomsk State University of Control Systems and Radioelectronics on the year 2013 with a degree in «Automation of technological processes and production». From 2013 to 2016 he completed the postgraduate program at Tomsk State University in direction of  «Mathematical and software for computers, complexes and computer networks». In 2016, defended his disseration for the degree of PhD in Engineering on the topic: «Algorithms for dynamically reconfigurable computing environments for image processing».

The main direction of scientific activity at present is the research and development of new methods and algorithms for computing vision systems, as well as their hardware implementation on computer systems with parallel-pipeline architecture. Since 2017, the practical direction of activity is the development of Autonomous сontrol systems for Unmanned vehicles, as well as the investigation of new approaches to the construction of visual navigation systems.

Publication list (more than 30 publications in Russian are not included here):

1. Shidlovskiy S.V., Sy'ryamkin V.I., Shashev D.V., Yurchenko A.V. Application of reconfigurable computing environments for image processing in X-ray tomography of materials //IOP Conf. Ser.: Mater. Sci. Eng. 2015. Vol. 81. P. 1-6.
2. Shidlovskii S.V., Shashev D.V. Morphological processing of binary images using reconfigurable computing environments //Optoelectronics, Instrumentation and Data Processing. 2015. Vol. 51, № 3. P. 227-233.
3. Borovik V.S., Shatravin V.V., Junusov I., Shashev D.V., Kornilov S.Y., Rempe N.G., Shidlovskiy S.V. Industrial Robot Automation in Solving Non-Vacuum Electron-Beam Welding Problems //MATEC Web of conferences. 2016. Vol. 79. P. 01034.
4. Shashev D.V., Shidlovskiy S.V. High-speed image processing systems in non-destructive testing //JPCS. 2017. Vol. 881. P. 012029.
5. Gorbachev S.V., Emelyanov S.G., Zhdanov D.S., Miroshnichenko S.Yu., Syryamkin V.I., Titov D.V., Shashev D.V. Digital Processingof Aerospace Images /ed.: Syryamkin V.I. London: Red Square Scientific, 2018. 244 p.
6. Shatravin V.V., Shashev D.V. Realization of the FPGA-based reconfigurable computing environment by the example of morphological processing of a grayscale image //IOP Conf. Ser.: Mater. Sci. Eng. 2018. Vol. 363. P. 012028.
7. Nguyen The. C., Shashev D.V. Methods and Algorithms for Detecting Objects in Video Files //MATEC Web of conferences. 2018. Vol. 155. P. 01016.
8. Taganov A.A., Shashev D.V. Simulation of the behavior of an unmanned aerial vehicle in virtual 3D scenes //IOP Conf. Ser.: Mater. Sci. Eng. 2019. Vol. 516. P. 012046.

Project list:

1. № 16-37-00082 “Algorithms and mathematical models of high-speed image processing systems” was funded by Russian Foundation for Basic Research.
2. № 16-29-04388 “Construction, design, modeling and experimental research of cognitive distributed image recognition systems and real-time control of a group of transport robots based on neuro-fuzzy, structurally-reconfigurable and correlation-extreme algorithms” was funded by Russian Foundation for Basic Research.
3. № 16-07-01138 “Intelligent reconfigurable control, navigation and image processing systems for autonomous mobile robots” was funded by Russian Foundation for Basic Research.
4. № 19-29-06078 “Development and research of reconfigurable high-speed image recognition algorithms for assessing the traffic situation on the basis of specialized mobile devices with parallel-pipeline architecture” was funded by Russian Foundation for Basic Research.
5. № 14.578.21.0241 “Development of autonomous intelligent system for unmanned aerial vehicle based on reconfigurable control, navigation and information processing algorithms and creation of a hardware and software complex for protection against small-sized aircrafts” was funded by Ministry of Science and Higher Education.
6. № SP-3573.2019.5 “Research and development of neural network algorithms for image classification and recognition that provide autonomous control of mobile robots” was funded by Grants Council of the President of the Russian Federation.
7. Project “Development of elements of hardware and software complex for small cargo delivery by a group of multirotor drones” was funded by Tomsk State University.