Kyrylo Smelyakov
Kyrylo Smelyakov
Head of the Department of Software Engineering, Member of STC, Deputy Head of the Section 2 of STC, Doctor of Technical Sciences, Professor Kharkiv National University of Radio Electronics
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A. Personal Statement
I am Doctor of Science, Professor, Head of the Department of Software Engineering at Kharkiv National University of Radio Electronics, Head of Data Science Lab.
My main scientific areas of interest:
1) Applied mathematics (mathematical modeling, algorithms and numerical methods, optimization)
2) Computer Science and
3) Data Science, including AI, ML and computer vision.
The main area of applied activity is interdisciplinary projects in the field of medical diagnostics. The main projects will be listed below.
As a result of many years of research, significant results have been obtained in the following key areas.
1) Enhancement of medical images (X-ray, CT, etc.) using linear and nonlinear gradational correction models. Including enhancement of low-contrast images and images of metallic objects with a gloss effect using interactive and automatic image processing methods.
2) Segmentation of objects in medical images, including processing of grayscale, color and low-contrast images.
3) Classification / detection of objects in medical images.
4) Development of medical diagnostic systems (including medical visualization systems), including for the effective analysis of gunshot wounds on CT, based on the analysis of images, image sets (CT) and video data.
All these results were obtained using hybrid image processing models, which are based on the combined use of classical models and artificial intelligence models, including neural networks, decision trees and clustering. The main research results have been published internationally. Author of more than 150 publications.
In recent years, I have successfully combined the functions of a researcher and a manager of research projects (RP), some of which had 10+ participants.
I lead a team of high-level professionals (in IT, AI, cyber security and applied mathematics) and have stable, extensive connections with colleagues from medical institutions for the effective implementation of interdisciplinary IT-medical projects of any complexity.
To summarize, I can make the following conclusion. I have the necessary knowledge, skills, experience, leadership qualities, motivation, a team of high-level professionals and the necessary connections with colleagues to successfully complete an interdisciplinary research project in the subject area.
Ongoing and recently completed projects that I would like to highlight include:
REWARD (Scientific PI)
01 Mar 2023 - 30 Sep 2024
Radio Electronics-Warwick Allied Research and Development
(University of Warwick, UK and Kharkiv National University of Radio Electronics, Ukraine)
0123U102783
InGuns-CT (PI), Role: co-investigator
31 May 2023 - 31 Dec 2024
Intelligent information and analytical system for diagnosing gunshot wounds on CT
(Re-granting of the Horizon 2020 program)
ZD2021/21210
NUMECO (Data Science PI)
04 May 2021 - 30 Apr 2022
Sustainable Digital Development of Economic Entities of the ECO Region
ОNE-YEAR MSC-BY-RESEARCH (Scientific PI)
1 Sep 2024 - 30 Sep 2026
Warwick-NURE MSc by Research in Computer Science
(University of Warwick, UK and Kharkiv National University of Radio Electronics, Ukraine)
Ibstech (PI)
01 Sep 2022 - now
The Next Generation of Image Based Search Technology
Main 10 citations in specific area for last years:
1. Smelyakov, K., Chupryna, A., Hvozdiev, M., Sandrkin, D., Ruban, I. & Voloshchuk, O. (2021). Unified models of gradation image correction. Book Chapter, Data-Centric Business and Applications, 293-317. doi: https://doi.org/10.1007/978-3-030-43070-2_14.
2. Smelyakov, K., Chupryna, A., Bohomolov, O. & Vakulik, E. (2022). Lung X-Ray Images Preprocessing Algorithms for COVID-19 Diagnosing Intelligent Systems. CEUR Workshop Proceedings, 3171, 1233-1250. http://ceur-ws.org/Vol-3171.
3. Smelyakov, K., Honchar, Y., Bohomolov, O. & Chupryna, A. (2022). Machine Learning Models Efficiency Analysis for Image Classification Problem. CEUR Workshop Proceedings, 3171, 942-959. http://ceur-ws.org/Vol-3171.
4. Smelyakov, K., Savulioniene, L., Chupryna, A., Sakalys, P. & Sandrkin, D. (2023). Adaptive Image Enhancement Model for the Robot Vision System, Vide. Tehnologija. Resursi - Environment, Technology, Resources, 3, 246-251. doi: https://doi.org/10.17770/etr2023vol3.7300.
5. Khoroshun, E., Smelyakov, K., Chupryna, A., Makarov, V., Nehoduiko, V., & Vakulik, Y. (2024). Improving of computed tomography images for effective diagnosis of gunshot wounds. EMERGENCY MEDICINE, 20(7), 577-583. https://doi.org/10.22141/2224-0586.20.7.2024.1776.
6. Vysotska, V., Smelyakov, K., Sharonova, N., Vakulik, E., Filipov, O. & Kotelnykov, R. (2024). Fast Color Images Clustering for Real-Time Computer Vision and AI System. CEUR Workshop Proceedings, 3664, 161-177. doi: 10.31110/COLINS/2024-1/012.
7. Cherednichenko, O., Kyrychenko, I., Nechvolod, K., Smelyakov, K., Dolhanenko, O. (2024). Data Security Analysis in EMM Systems. CEUR Workshop Proceedings, 3668, 133-144. Doi: 10.31110/COLINS/2024-2/010.
8. Smelyakov, K., Kitsenko, Y., & Chupryna, A. (2024). Deepfake Detection Models Based on Machine Learning Technologies. 2024 IEEE Open Conference of Electrical, Electronic and Information Sciences (eStream), 1-6. doi: 10.1109/eStream61684.2024.10542582.
9. Shcherban, Y., Smelyakov, K. & Chupryna, A. (2024). AI Models of Pulmonary Sarcoidosis Detection. 2024 IEEE Open Conference of Electrical, Electronic and Information Sciences (eStream), 1-4. doi: 10.1109/eStream61684.2024.10542583.
10. Byzkrovnyi, O., Smelyakov, K., Chupryna, A. & Lanovyy, O. (2024). Comparison of Object Detection Algorithms for the Task of Person Detection on Jetson TX2 NX Platform. 2024 IEEE Open Conference of Electrical, Electronic and Information Sciences (eStream), 1-6. doi: 10.1109/eStream61684.2024.10542592.
B. Positions, Scientific Appointments, and Honors
Positions and Scientific Appointments
2024 – Present
Head of the Department of Software Engineering, Kharkiv National University of Radio Electronics, Ukraine
2023 (Jul – Aug)
Visiting Professor, University of Warwick, UK
2020 – 2024
Professor, Software Engineering Department, Kharkiv National University of Radio Electronics, Ukraine
2017 – 2020
Professor, Electronic Computers Department, Kharkiv National University of Radio Electronics, Ukraine
2013 – 2017
Professor, Mathematical and Software Department, Kharkiv National University of Air Force, Ukraine
2005 – 2013
Associate Professor, Mathematical and Software Department, Kharkiv National University of Air Force, Ukraine
2004 – 2005
Assistant, Informatics Department, Kharkiv National University of Radio Electronics, Ukraine
2001 – 2004
Graduate Student, Informatics Department, Kharkiv National University of Radio Electronics, Ukraine
2001 (Jul – Oct)
Researcher, Software Engineering Department, Kharkiv National University of Radio Electronics, Ukraine
2019 – Present
Expert of the National Agency for Higher Education Quality Assurance (Ukraine)
Honors 2020 Acknowledgments of the Ministry of Education and Science of Ukraine
C. Contributions to Science
My earlier and more publications mainly focus on various aspects of intelligent data analysis systems development, digital image processing, image retrieval in big data repositories, and text processing. The main ones (just international) are listed below.
1. Intelligent data analysis systems.
a. Smelyakov, K., Pribylnov, D., Martovytskyi, V. & Chupryna, A. (2018). Investigation of network infrastructure control parameters for effective intellectual analysis. 2018 14th International Conference on Advanced Trends in Radioelecrtronics, Telecommunications and Computer Engineering (TCSET), Lviv-Slavske, Ukraine, 983-986, doi: 10.1109/TCSET.2018.8336359.
b. Byzkrovnyi, O., Smelyakov, K. & Chupryna, A. (2022). Approaches for Cryptocurrency Price Prediction, 2022 IEEE 9th International Conference on Problems of Infocommunications, Science and Technology (PIC S&T), Kharkiv, Ukraine, 75-80, doi: 10.1109/PICST57299.2022.10238480.
c. Smelyakov, K., Bohomolov, O., Kizitskyi, M. & Chupryna, A. (2022). Identification of Modern Facial Emotion Recognition Models. CEUR Workshop Proceedings, 3171, 1267-1281. http://ceur-ws.org/Vol-3171.
d. Teslenko, D., Sorokina, A., Smelyakov, K. & Filipov, O. (2023). Comparative Analysis of the Applicability of Five Clustering Algorithms for Market Segmentation, 2023 IEEE Open Conference of Electrical, Electronic and Information Sciences (eStream), Vilnius, Lithuania, 1-6, doi: 10.1109/eStream59056.2023.10134796.
e. Smelyakov, K., Hurova, Y. & Osiievskyi, S. (2023). Analysis of the Effectiveness of Using Machine Learning Algorithms to Make Hiring Decisions. CEUR Workshop Proceedings, 3387, 77-92. https://ceur-ws.org/Vol-3387.
f. Smelyakov, K., Klochko, O. & Dudar, Z. (2023). Building Quantile Regression Models for Predicting Traffic Flow. CEUR Workshop Proceedings, 3387, 117-132. https://ceur-ws.org/Vol-3387
g. Sakalys, P., Loreta, S., Savulionis, D., Chupryna, A. & Smelyakov, K. (2024). Research of Robotic System Positioning Accuracy // Vide. Tehnologija. Resursi - Environment, Technology, Resources, 3, 279-282. doi: https://doi.org/10.17770/etr2024vol3.8156.
2. Digital image processing.
a. Smelyakov, K., Chupryna, A., Yeremenko, D., Sakhon, A. & Polezhai, V. (2018). Braille Character Recognition Based on Neural Networks. 2018 IEEE Second International Conference on Data Stream Mining & Processing (DSMP), Lviv, Ukraine, 509-513. doi: 10.1109/DSMP.2018.8478615.
b. Ruban, I., Smelyakov, K., Vitalii, M., Dmitry, P. & Bolohova, N. (2018). Method of neural network recognition of ground-based air objects. 2018 IEEE 9th International Conference on Dependable Systems, Services and Technologies (DESSERT), Kyiv, UKraine, 589-592. doi: 10.1109/DESSERT.2018.8409200.
c. Arsenov, A., Ruban, I., Smelyakov, K. & Chupryna, A. (2018) Evolution of convolutional neural network architectursae in image classification problems. CEUR Workshop Proceedings, 2318, 35-45. https://ceur-ws.org/Vol-2318.
d. Bielievtsov, S., Ruban, I., Smelyakov, K. & Sumtsov, D. (2018). Network technology for transmission of visual information. CEUR Workshop Proceedings, 2318, 160-175. https://ceur-ws.org/Vol-2318.
e. Smelyakov, K., Datsenko, A., Skrypka, V. & Akhundov, A. (2019). The Efficiency of Images Reduction Algorithms with Small-Sized and Linear Details. 2019 IEEE International Scientific-Practical Conference Problems of Infocommunications, Science and Technology (PIC S&T), 745-750, doi: 10.1109/PICST47496.2019.9061250.
f. Smelyakov, K., Hvozdiev, M., Chupryna, A., Sandrkin, D. & Martovytskyi, V. (2019). Comparative Efficiency Analysis of Gradational Correction Models of Highly Lighted Image. 2019 IEEE International Scientific-Practical Conference Problems of Infocommunications, Science and Technology (PIC S&T), 703-708, doi: 10.1109/PICST47496.2019.9061356.
g. Smelyakov, K., Tovchyrechko, D., Ruban, I., Chupryna, A. & Ponomarenko, O. (2019). Local Feature Detectors Performance Analysis on Digital Image. 2019 IEEE International Scientific-Practical Conference Problems of Infocommunications, Science and Technology (PIC S&T), 644-648, doi: 10.1109/PICST47496.2019.9061331.
h. Smelyakov, K., Shupyliuk, M., Martovytskyi, V., Tovchyrechko, D. & Ponomarenko, O. (2019). Efficiency of image convolution. 2019 IEEE 8th International Conference on Advanced Optoelectronics and Lasers (CAOL), 578-583, doi: 10.1109/CAOL46282.2019.9019450.
i. Smelyakov, K., Chupryna, A., Hvozdiev, M. & Sandrkin, D. (2019). Gradational Correction Models Efficiency Analysis of Low-Light Digital Image. 2019 Open Conference of Electrical, Electronic and Information Sciences (eStream), 1-6, doi: 10.1109/eStream.2019.8732174.
j. Smelyakov, K., Chupryna, A., Bohomolov, O. & Ruban, I. (2020). The Neural Network Technologies Effectiveness for Face Detection. 2020 IEEE Third International Conference on Data Stream Mining & Processing (DSMP), 201-205, doi: 10.1109/DSMP47368.2020.9204049.
k. Smelyakov, K., Smelyakov, S. & Chupryna, A. (2020). Advances in Spatio-Temporal Segmentation of Visual Data. Chapter 1. Adaptive Edge Detection Models and Algorithms. – Springer Nature Switzerland AG 2020, 1-51. DOI:10.1007/978-3-030-35480-0_1.
l. Smelyakov, K., Chupryna, A., Bohomolov, O. & Hunko, N. (2021). The Neural Network Models Effectiveness for Face Detection and Face Recognition. 2021 IEEE Open Conference of Electrical, Electronic and Information Sciences (eStream), 1-7, doi: 10.1109/eStream53087.2021.9431476.
m. Byzkrovnyi, O., Savulioniene, L., Smelyakov, K., Sakalys, P. & Chupryna, A. (2023). Comparison of Potential Road Accident Detection Algorithms for Modern Machine Vision System, Vide. Tehnologija. Resursi - Environment, Technology, Resources, 3, 50-55. doi: https://doi.org/10.17770/etr2023vol3.7299.
n. Byzkrovnyi, O., Chupryna, A., Smelyakov, K., Sharonova, N. & Repikhov, V. (2023). Comparison of Object Detection Algorithms for the Task of Detecting Possible Road Accident, CEUR Workshop Proceedings, 3387, 13-28. https://ceur-ws.org/Vol-3387.
3. Image retrieval in big data repositories.
a. Smelyakov, K., Sandrkin, D., Ruban, I., Vitalii, M. & Romanenkov, Y. (2018). Search by Image. New Search Engine Service Model. 2018 International Scientific-Practical Conference Problems of Infocommunications. Science and Technology (PIC S&T), Kharkiv, Ukraine, 181-186, doi: 10.1109/INFOCOMMST.2018.8632117.
b. Smelyakov, K., Chupryna, A., Ponomarenko, O. & Kolisnyk, M. (2020). Search by Image Engine using Local Feature Detectors, 2020 IEEE Open Conference of Electrical, Electronic and Information Sciences (eStream), Vilnius, Lithuania, 1-4, doi: 10.1109/eStream50540.2020.9108884.
c. Smelyakov, K., Chupryna, A., Sandrkin, D. & Kolisnyk, M. (2020). Search by Image Engine for Big Data Warehouse. 2020 IEEE Open Conference of Electrical, Electronic and Information Sciences (eStream), Vilnius, Lithuania, 1-4, doi: 10.1109/eStream50540.2020.9108782.
d. Pohuliaiev, Y., Smelyakov, K., Chupryna, A. & Ruban, I. (2022). Methods of Semantic Structured Search," 2022 IEEE 9th International Conference on Problems of Infocommunications, Science and Technology (PIC S&T), Kharkiv, Ukraine, 101-105, doi: 10.1109/PICST57299.2022.10238538.
e. Smelyakov, K., Prokopenko, O. & Chupryna, A. (2022). Object-Based Image Comparison Algorithm Development for Data Storage Management Systems. CEUR Workshop Proceedings, 3171, 1251-1266. http://ceur-ws.org/Vol-3171.
f. Kyrychenko, I., Tereshchenko, G. & Smelyakov, K. (2024). Optimized Indexing Method in a Hybrid Image Storage Model for Efficient Storage and Access in Big Data Environments. 2024 IEEE 17th International Conference on Advanced Trends in Radioelectronics, Telecommunications and Computer Engineering (TCSET), Lviv, Ukraine, 1-4, doi: 10.1109/TCSET64720.2024.10755763.
4. Text processing.
a. Smelyakov, K., Karachevtsev, D., Kulemza, D., Samoilenko, Y., Patlan, O. & Chupryna, A. (2020). Effectiveness of Preprocessing Algorithms for Natural Language Processing Applications. 2020 IEEE International Conference on Problems of Infocommunications. Science and Technology (PIC S&T), Kharkiv, Ukraine, 187-191, doi: 10.1109/PICST51311.2020.9467919.
b. Dashenkov, D., Smelyakov, K. & Turuta, O. (2021). Methods of Multilanguage Question Answering. 2021 IEEE 8th International Conference on Problems of Infocommunications, Science and Technology (PIC S&T), Kharkiv, Ukraine, 251-255, doi: 10.1109/PICST54195.2021.9772145.
c. Smelyakov, K., Chupryna, A., Darahan, D. & Midina, S. (2021). Effectiveness of modern text recognition solutions and tools for common data sources. CEUR Workshop Proceedings, 2870, 154–165, https://ceur-ws.org/Vol-2870.
d. Danylenko, S., Smelyakov, K. & Chupryna, A. (2022). Methods of Digital-To-Analog Conversion for Reproduction of Sound Waves. 2022 IEEE 9th International Conference on Problems of Infocommunications, Science and Technology (PIC S&T), Kharkiv, Ukraine, 43-48, doi: 10.1109/PICST57299.2022.10238632.
e. Dashenkov, D., Smelyakov, K. & Sharonova, N. (2023). Dataset for NLP-enhanced image classification. CEUR Workshop Proceedings, 3396, 88-101. https://ceur-ws.org/Vol-3396.
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