Ravil Muhamedyev

Ravil Muhamedyev

Doctor of technical sciences


Institute of Automation and Information Technologies

Department of Software Engineering

Email: r.mukhamediev@satbayev.111


PhD count:

Professional biography

Since 2018 - Satbayev University, Professor, DEP. PI

2017 – Director of the IITT KazNITU after named K. Satbayev, Professor, DEP. BOIL

2016 -2017 Professor of Information System Management Department of Kazakh British Technical University,

2013 - senior researcher, Institute of information and computing technologies MES

2012-2015 head of the Department will Stpoit international information technologies University (IITU), Professor

2010-2011 – head of the IT Department of the International University of information technology (IITU), Professor

2007-2010 head of the Department of Natural Sciences and information technologies of the Institute of information management systems (ISMA), associate Professor

Since 2006 – associate Professor (ISMA)

2005-2006-head of information projects Department (ISMA)

2001-2004-associate Professor (ISMA)

1996-2000-Deputy Director of computer science at the 80th Riga secondary school

1992-1995-associate Professor (Riga Aviation University)

1987-1991-Assistant (Riga Institute of civil aviation engineers)

1986-1987-engineer of the Department of operation of aviation radio-electronic equipment of Riga Institute of civil aviation engineers

1983-1986-post-graduate student (Riga Institute of civil aviation engineers)


2021 – Full professor in Informatics, Computer engineering and control (Diploma № PR 0000129, Decision of the Committee for Quality Assurance in Education and Science of the Ministry of Education and Science of the Republic of Kazakhstan, order No. 651 of August 10, 2021)

2017-Professor (Decision no. 03.03-11-2017 Committee for awarding degrees and titles in the field of Natural Sciences and Information Technology)

2013-Professor (Decision Nr. 219 of the Committee for awarding degrees and titles - Promotion Council " RTU P-07” in Information Technologies, Riga, Latvia)

2006-Associate Professor (Decision of the RTU faculty Council N 116).

1993-doctor of engineering, diploma G-D Nr. 000088 (Latvia) (05.25.05)

1992-associate Professor, diploma Nr. 003380 (Russian Academy of Sciences)

1987-Candidate of technical Sciences, the Nr diploma. 098882. Topic: "automation of management processes for the technical operation of ground-based aviation radio-electronic equipment»

1983-1986 – post-graduate student. The objects of research are the use of computer technologies in the operation of radio equipment and improving reliability, and the use of database technologies to assess the reliability of radio equipment.

In 1983, he graduated from the Riga Institute of civil aviation engineers. Faculty of aviation radio equipment. Qualification-radio engineer, diploma Nr.365663.

Scientific projects

Programming, artificial intelligence and intelligent systems (machine learning), computer training and testing, simulation of asynchronous systems.

Management of software and scientific projects;  Innovative projects using artificial intelligence technologies and algorithms.

Current projects (see https://geoml.info/):

–AP14869972, Development and adaptation of computer vision and machine learning methods for solving precision agriculture problems using unmanned aerial systems, AP14869972 (2022-2024)

–BR18574144, Development of a data mining system for monitoring dams and other engineering structures under the conditions of man-made and natural impacts (2022-2024)

- AP08856412, Development of Intelligent Data Processing and Flight Planning Models for Precision Farming Tasks Using UAVs (2020-2022), https://geoml.info/?page_id=686&lang=en

- AP09259587, Developing methods and algorithms of intelligent GIS for multi-criteria analysis of healthcare data, (2021-2023), https://geoml.info/?page_id=710&lang=en

- BR18574144, Space monitoring and GIS for quantifying soil salinity and degradation of agricultural land in southern Kazakhstan (2021-2023), https://geoml.info/?page_id=823&lang=en

- ADVANCED CENTRE FOR PHD STUDENTS AND YOUNG RESEARCHERS IN INFORMATICS (ACESYRI), 610166-EPP-1-2019-1-SK-EPPKA2-CBHE-JP, Erasmus+ ,  https://satbayev.university/en/acesyri


Mukhamediev R. I. Yakunin, K., Aubakirov, M., Assanov, I., Kuchin, Y., Symagulov, A., Levashenko V., Zatceva E., Sokolov D., Amirgaliyev, Y. . Coverage path planning optimization of heterogeneous UAVs group for precision agriculture //IEEE Access. – 2023. – Т. 11. – №. 15. – С. 5789-5803, doi: 10.1109/ACCESS.2023.3235207, https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10011226

Yakunin, K.; Mukhamediev, R.I.; Yelis, M.; Kuchin, Y.; Symagulov, A.; Levashenko, V.; Zaitseva, E.; Aubakirov, M.; Yunicheva, N.; Muhamedijeva, E.; Gopejenko, V.; Popova, Y. Analysis of the Correlation between Mass-Media Publication Activity and COVID-19 Epidemiological Situation in Early 2022 //Information. – 2022. – Т. 13. – №. 9. – С. 434.  https://doi.org/10.3390/info13090434

Mukhamediev, R. I., Popova, Y., Kuchin, Y., Zaitseva, E., Kalimoldayev, A., Levashenko V., Symagulov, A., Abdoldina F., Gopejenko V., Yakunin K., Muhamedijeva E., Yelis, M. Review of Artificial Intelligence and Machine Learning Technologies: Classification, Restrictions, Opportunities and Challenges //Mathematics. – 2022. – Т. 10. – №. 15. – С. 2552. https://doi.org/10.3390/math10152552

Mukhamediev R. I., Kuchin, Y. et al. Estimation of Filtration Properties of Host Rocks in Sandstone-type Uranium Deposits Using Machine Learning Methods //IEEE Access. – 2022. – T.10. –  C.18855-18872. DOI 10.1109/ACCESS.2022.3149625; https://ieeexplore.ieee.org/abstract/document/9706226

Kirill Yakunin, Ravil I. Mukhamediev, Elena Zaitseva , Vitaly Levashenko, Marina Yelis, Adilkhan Symagulov, Yan Kuchin, Elena Muhamedijeva, Margulan Aubakirov and Viktors Gopejenko. Mass media as a mirror of the COVID-19 pandemic // Computation 2021, 9(12), 140; https://doi.org/10.3390/computation9120140

Mukhamediev R. I. et al. Review of Some Applications of Unmanned Aerial Vehicles Technology in the Resource-Rich Country //Applied Sciences. – 2021. – Т. 11. – №. 21. – С. 10171. https://doi.org/10.3390/app112110171

Л. Л. Садовская, А. Е. Гуськов, Д.В. Косяков, Р. И. Мухамедиев. Обработка текстов на естественном языке: обзор публикаций//Иcкусственный интеллект и принятие решений.- 3/2021  c. 95-115, DOI 10.14357/20718594210306

Mukhamediev R. I. et al. From Classical Machine Learning to Deep Neural Networks: A Simplified Scientometric Review //Applied Sciences. – 2021. – Т. 11. – №. 12. – С. 5541. https://doi.org/10.3390/app11125541

Yakunin K. et al. KazNewsDataset: Single Country Overall Digital Mass Media Publication Corpus //Data. – 2021. – Т. 6. – №. 3. – С. 31. https://doi.org/10.3390/data6030031

Mukhamediev R. I. et al. Classification of Negative Information on Socially Significant Topics in Mass Media //Symmetry. – 2020. – Т. 12. – №. 12. – С. 1945. https://doi.org/10.3390/sym12121945

R. Muhamedyev, K. Yakunin, YA. Kuchin, A. Symagulov, S. T. Buldybayev ,S. Murzahmetov and A. Abdurazakov. The use of machine learning "black boxes" explanation systems to improve the quality of school education //Cogent Engineering. – 2020. – Т. 7. – №. 3. – С. 1518571  https://doi.org/10.1080/23311916.2020.1769349

Kuchin Y. I., Mukhamediev R. I., Yakunin K. O. One method of generating synthetic data to assess the upper limit of machine learning algorithms performance //Cogent Engineering. – 2020. – Т. 7. – №. 1. – С. 1718821.  https://doi.org/10.1080/23311916.2020.1718821

Kuchin Y. et al. Assessing the Impact of Expert Labelling of Training Data on the Quality of Automatic Classification of Lithological Groups Using Artificial Neural Networks //Applied Computer Systems. – 2020. – Т. 25. – №. 2. – С. 145-152. https://sciendo.com/pdf/10.2478/acss-2020-0016

Р. И. Мухамедиев, Я. И. Кучин, К. О. Якунин, Е. Л. Мухамедиева, С. В. Костарев Предварительные результаты оценки литологических классификаторов для урановых месторождений пластово-инфильтрационного типа //Cloud of Science. – 2020. – Т. 7. – №. 2. – С. 258-272.

R. I. Mukhamediev et al. Multi-Criteria Spatial Decision Making Supportsystem for Renewable Energy Development in Kazakhstan // IEEE Access.-2019.- T. 7.- c. 122275-122288. https://doi.org/10.1109/ACCESS.2019.2937627

Mukhamedyev R. et al. Assessment of the dynamics of publication activity in the field of natural language processing and deep learning //International Conference on Digital Transformation and Global Society. – Springer, Cham, 2019. – С. 130-135.

Muhamedyev R. et al. New bibliometric indicators for prospectivity estimation of research fields //Annals of Library and Information Studies (ALIS). – 2018. – Т. 65. – №. 1. – С. 62-69. http://nopr.niscair.res.in/handle/123456789/44217

Mukhamediev R. I., Aligulyev R. M., Muhamedijeva J. Estimation of Relationship Between Domains of ICT Semantic Network //International Conference on Digital Transformation and Global Society. – Springer, Cham, 2017. – С. 130-135.

Muhamedyev R. et al. Visualization of the Renewable Energy Resources //International Conference on Augmented Reality, Virtual Reality and Computer Graphics. – Springer International Publishing, 2016. – С. 218-227.

Muhamedyev R. Machine learning methods: An overview //CMNT. - 19(6). – 2015. - P. 14-29.

Muhamedyev R. et al. Comparative analysis of classification algorithms //Application of Information and Communication Technologies (AICT), 2015 9th International Conference on. – IEEE, 2015. – P. 96-101.

Muhamediyev R. I., Amirgaliyev Y., Iskakov S. K. Integration of Results from Recognition Algorithms Applied to the Uranium Deposits (Selected Papers from The 6th International Conference on Soft Computing and Intelligent Systems and The 13th International Symposium on Advanced Intelligent Systems (SCIS&ISIS2012)) //Journal of advanced computational intelligence and intelligent informatics. – 2014. – Т. 18. – №. 3. – P. 347-352.

Muhamedyev R. et al. Optimization of medical information systems by using additional factors //Computer Modelling and New Technologies. – 2014. – Т. 18. – №. 1. – С. 100-108.

Amirgaliev E. et al. Recognition of rocks at uranium deposits by using a few methods of machine Learning //Soft Computing in Machine Learning. – Springer International Publishing, 2014. – С. 33-40.

Амиргалиев Е.Н., Искаков С.Х., Кучин Я.В., Мухамедиев Р.И. Интеграция алгоритмов распознавания литологических типов. Журнал "Проблемы информатики",Сибирское отделение РАН, N 4(21) 2013, c. 11-20, ISSN 2073-0667(VINITI)

Амиргалиев Е.Н., Искаков С.Х., Кучин Я.В., Мухамедиев Р.И.  Методы машинного обучения в задачах распознавания пород на урановых месторождениях. //Известия НАН РК , 2013,  №3.  С.82-88.

Potential research studies of doctoral students

Machine Learning, Natural Language processing, Artificial Intelligence, Computer Vision, Scientometrics (bibliometrics)