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Department of Digital Economy and System Analysis
Department of Digital Economy and System Analysis
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Department of Digital Economy and System Analysis
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Scientific Work

of Digital Economy and System Analysis

1. Scientific and pedagogical staff

The Department of Digital Economics and System Analysis employs 19 full-time faculty members, 94.7% of whom have a degree:

- doctors of sciences, professors
1. Roskladka A., Doctor of Science (Economics), PhD in Physics and Mathematics

1. Expert of the National Agency for Quality Assurance in Higher Education for accreditation of educational programs in the specialties 051 “Economics”, 113 “Applied Mathematics” and 124 “Systems Analysis”.
2. Member of the Scientific Council of the Ministry of Education and Science of Ukraine (Section 2 “Informatics and Cybernetics”).
3. Member of the working group on the development of the National Strategy for the Development of Artificial Intelligence in Ukraine (2021-2030).
4. Member of the Scientific, Methodological, Editorial, Scientific Expert Council of SUTE, member of the Quality Council of SUTE. 
5. Member of the Academic Council of the Faculty of Information Technology of SUTE.
6. Guarantor of the program “Information Technology and Business Analytics (Data Science)”, specialty 124 “System Analysis” (Master's degree).
7. Member of the support group of the specialty 051 “Economics” (educational and scientific level PhD).

2. Hamalii V., Doctor of Sciences in Physics and Mathematics

1. Member of the Council of SUTE's staff.
2. Member of the Academic Council of the Faculty of Information Technologies of SUTE.
3. Guarantor of the EP “Digital Economy”, specialty 051 “Economics” (Master's degree).
4. Member of the support group of specialty 122 “Computer Science” (educational and scientific level PhD)
5. Academician of the Academy of Economic Sciences of Ukraine

3. Kartashova S., Doctor of Sciences (Biology), PhD in Physics and Mathematics

1. Member of the Academic Council of the Faculty of Information Technologies of SUTE.

- PhDs, associate professors (58,1%):
1. Bielova M., PhD in Physics and Mathematics
2. Geseleva N., PhD in Technical Sciences

1. Member of the Academic Council of the Faculty of Information Technology of SUTE.

3. Denysenko V., PhD in Physics and Mathematics

1. Member of the Academic Council of the Faculty of Information Technology of SUTE.

4. Zozulia V., PhD in Technical Sciences

1. Vice-Academician of the Academy of Technical Sciences of Ukraine 

5. Ivanova O., PhD in Economics

1. Member of the Staff Council of SUTE
2. Member of the Academic Council of the Faculty of Information Technology of SUTE.
3. Guarantor of EP & laquo;Digital Economy» specialty 051 & laquo;Economics» Bachelor's degree

6. Kulazhenko V., PhD in Economics
1. Guarantor of the educational program "Information Technology and Business Analytics (Data Science)" first (bachelor's) cycle of higher education
2. Member of the Academic Council of the Faculty of Information Technology of SUTE
7. Kulyk А., PhD in Economics

1. Гарант освітньо програми 1-го (бакалаврського) рівня вищої освіти "Комп'ютерне та математичне моделювання"

8. Makoiedova V., PhD in Computer Sciences
9. Kotliar V., PhD in Physics and Mathematics
10. Mitsenko S., PhD in Technical Sciences

1. Член Вченої ради факультету інформаційних технологій ДТЕУ

11. Mykhailenko S., PhD in Physics and Mathematics
12. Stolietova І., PhD in Economics

1. Member of the Council of the SUTE staff
2. Member of the Academic Council of the Faculty of Information Technologies of SUTE

- PhDs, non-academic titles (21,1%):
1. Лазоренко В. В., кандидат економічних наук

1. Член ради трудового колективу ДТЕУ
2. Член вченої ради факультету інформаційних технологій ДТЕУ.

2. Лапига І. В., кандидат педагогічних наук
3. Міщенко А. О, кандидат економічних наук
- teachers without a scientific degree (5,2%):
1. Тарасюк А. М.
2. Current Department (initiative) R&D activities
3. Scientific cooperation
Установа-партнер Тема 
співробітництва
Документ, в рамках якого
здійснюється співробітництво,
термін його дії
Практичні результати
від співробітництва
Братиславський університет економіки та менеджменту
м. Братислава, Словаччина
Співпраця в рамках спільної магістерської програми «Міжнародна бізнес-аналітика» Угода № 107 від 02.07.2018 Спільна магістерська програми, закордонне стажування науково-педагогічних працівників
ТОВ «ПРОКОМ»,
м. Київ
Залучення досвіду та впровадження професійних компетентностей Меморандум про співпрацю № 29 від 12.03.2018. Удосконалення існуючих освітніх програм
ТОВ «БіДжіЕс Сервіс-Центр»,
м. Київ
Сприяння інформаційному обміну за видами діяльності сторін Договір про співробітництво №30 від 12.03.2018 Підвищення кваліфікації, стажування фахівців
4. Scientific events

Протягом 2023 року викладачі кафедри цифрової економіки та системного аналізу взяли участь у 19 конференціях (в межах України - 18, за межами України - 1).

Проведені лекції, майстер-класи, тренінги за участю стейкголдерів:

з/п
ПІБ
(вчене звання, науковий ступінь, посада, місце роботи)
Назва 
(лекції, майстер-класу, тренінгу)
Дата
проведен
ня
1 Ольга Лугова, незалежний бізнес-аналітик, голова громадської організації «Українська асоціація «ODOO» Лекція на тему: «Використання платформи ODOO для оптимізації бізнес-рішень у роботі аналітика» 01.03.2023
2 Лілія Дехтяр, HR-менеджер, «IT Specialist» Лекція на тему: «Новітні концепції IT рішень у період воєнного стану в Україні» 07.04.2023
3 Лілія Дехтяр, HR-менеджер, «IT Specialist» Лекція на тему: «Новітні концепції IT рішень в Україні» 30.10.2023
4 Ольга Лугова, незалежний бізнес-аналітик, голова громадської організації «Українська асоціація «ODOO» Лекція на тему: «CRM-ERP-система Odoo як альтернатива російським програмним продуктам » 16.11.2023
5. Scientific and educational publications, inventive activity

Протягом 2023 року викладачі кафедри стали авторами 14 публікацій у наукометричних базах Scopus та Web of Science (д.е.н., проф. Роскладка А. А., д.ф.-м.н., проф. Гамалій В. Ф., д.б.н., к.ф.-м.н., професор Карташова С.С., к.т.н., доц. Геселева Н.В., к.т.н., доц. Зозуля В.А., к.т.н., доц. Міценко С. А., к.е.н, доц. Міщенко А.О., к.е.н., доц. Столєтова І.Г., к.ф.-м.н., доц. Бєлова М.О., к.ф.-м.н., доц. Денисенко В.І., к.ф.-м.н., доц. Ковальчук Т.В., к.ф.-м.н., доц. Котляр В.Ю., к.ф.-м.н., доц. Михайленко С.В.)

6. Thesis development by PhD students
Name Thesis title

Scientific   Supervisor

Start date Terms of defense
1 Tarasiuk A. Intelligent management system for agricultural companies Hamalii V.
D. in Physics and Mathematics, Prof.
01.10.2019 Jan. 2024
2 Diachenko М. Intelligent system for processing customer support requests Roskladka. А., D. in Economics, Prof. 01.04.2021 Dec.2025
3 Postrelko Y.  Intelligent system for analyzing traffic flows in the city Roskladka. А., D. in Economics, Prof. 01.10.2022 Dec.2026
4 Pryhoda А. Design and development of a microservice architecture-based CRM system Roskladka. А., D. in Economics, Prof. 01.10.2022 Dec.2026
5 Kuzin О. Modeling the resilient information environment of a bank Roskladka. А., D. in Economics, Prof. 01.10.2023 Dec.2027
6 Otmorskyi М. Digital technologies for analyzing human behavior Roskladka. А., D. in Economics, Prof. 01.10.2023 Dec.2027
7 Katrecha L. Information technology for automation of specialized management of healthcare institutions Mitsenko S., PhD in Technical Sciences, Assoc. Prof. 01.10.2023 Dec.2027
8 Palii V. Modeling processes in an information system based on Agile technology Mitsenko S., PhD in Technical Sciences, Assoc. Prof. 01.10.2023 Dec.2027
9 Sikora R. Modeling of microservice architecture of e-commerce information system Mitsenko S., PhD in Technical Sciences, Assoc. Prof. 01.10.2023 Dec.2027
7. Information on research and innovation activities of students and young scientists

During 2023:

  • 21 scientific publications with the participation of students were published:
  • 12 students participated in 11 conferences;
  • 9 students took part in a research competition.
8. Scopus scientometric indicators ( academic staff at the main place of work in SUTE)
Name ID Scopus Number of
of publications in
Scopus
Number of
of citations in
Scopus
H-index
Scopus
Roskladka.А. 14062340300 11 32 4
Bielova М.  36817339100 12 42 4
Hamalii V. 6603224194 17 21 3
Zozulia V. 55843835200 12 24 2
Geseleva N. 56658715600 5 13 2
Kovalchuk Т. 57199685221 6 8 2
Kotliar V. 7005605392 28 18 2
Mykhailenko S. 7005594254 6 6 2
Kulazhenko V. 57208321112 2 4 1
Mitsenko S. 57204913015 6 5 1
Stolietova I. 57222546565 1 2 1
Denysenko V. 7006384997 5 15 1
Ivanova О. 56529067200 3 3 1
Lapyha І.  57211386938 1 - -
In total by department 115
(+6 in 2023)
193
(+13 in 2023)
26
(+3 in 2023)

Official account of the Department of Digital Economy and System Analysis at Google Scholar : Google Scholar.

TRENDS IN THE DEVELOPMENT OF SCIENTIFIC DIRECTIONS OF THE DEPARTMENT OF DIGITAL ECONOMY AND SYSTEM ANALYSIS 

 The Department of Digital Economy and System Analysis carries out research in two main areas:

  • Data Science;
  • mathematical and computer modeling of digital economy processes. 

Data Science

The amount of information in the world has reached enormous proportions. This is eloquently evidenced by the fact that 90% of the data acquired by mankind during its existence was received in the last two years, and by the end of 2020 this amount of information will double and reach an unprecedented value of 40,000 exabytes.

Data Science is an interdisciplinary field of scientific methods, processes and systems related to the extraction of knowledge from data in various forms (both structured and unstructured). 

It combines fields such as mathematics, statistics, computer science, machine learning etc. A Data Science professional is distinguished by extensive cross-disciplinary knowledge and super-ability to analyze. 

Glassdoor, the most authoritative website with the information about the work, which annually publishes the 50 most relevant professions in the United States, prefers the data analysis specialists for four years in a row.

According to the latest World Economic Forum report in 2022, 85% of companies in the world will need, first of all, data analysis specialists. Among the professional areas that are actively included in all areas of activity, it is data analytics, work with big data, artificial intelligence and machine learning. 

In 2019, the World Economic Forum report on the importance of Data Science in the global economy was published. Real data on the need for Data Science Skills in all areas of human activity were given. 

Main directions of the Department’s research in the field of Data Science: 

  • comprehensive business analysis of complex systems of different nature based on Data Science methodology; 
  • construction and analysis of expert systems and artificial intelligence systems; 
  • development and systematic analysis of machine learning methods and algorithms for business process optimization; 
  • identification of basic data that affect the development of physical, economic, and social processes; the extraction of stochastic and uncertain factors and the study of relationships between them; 
  • solving problems of intellectual analysis of big data in various fields of science, technology, finance, socio-economic and political spheres and the national economy as a whole; 
  • computer implementation of mathematical models of real processes and systems; 
  • use of data analysis software (Power BI, Tableau, RapidMiner), universal and specialized programming languages (C #, Java, Python, R, SQL), simulation languages for system research. 

Main scientific publications of the Department’s academic staff in the field of Data Science: 

  1. Roskladka A. The data science tools for research of emigration processes in Ukraine / A. Roskladka, N. Roskladka, G. Kharlamova, A. Karpuk, A. Stavytskyy // Problems and Perspectives in Management - Volume 18, issue #1, 2020, p. 70-81 (Scopus).
  2. Roskladka A. Data analysis and forecasting of tourism development in Ukraine / A.Roskladka, N. Roskladka, O. Dluhopolskyi, G. Kharlamova, M. Kiziloglu // Innovative Marketing. - Volume 14, 2018, issue #4, pp. 19-33 (Scopus).
  3. Roskladka A. Data Scientist: a glance into the future / A. Roskladka, O. Ivanova, V. Kulazhenko // Зовнішня торгівля: економіка, фінанси, право. – 2019. – № 3. – C. 109- 120.
  4. Роскладка А. А Кластерний аналіз клієнтської бази даних підприємств сфери послуг / А.А. Роскладка,Н.О. Роскладка, О. О. Дзигман // Агросвіт, 2019. – №16. – С. 8-17.
  5. Роскладка А. А. Моделювання процесу консолідації даних агропромислового підприємства / А.А. Роскладка // Вісник Одеського національного університету. – 2015. – № 20 (2/1). – С. 191-194.
  6. Roskladka A. Practical implementation of the methodology of forming a system for monitoring the process of information support / A. Roskladka, R. Baglai, V. Lazurenko, M. Zaichenko // Big Data Processing: methods, models and information technologies: monograph. – Shioda GmbH, Steyr, Austria, 2019. – P. 161-188.
  7. Roskladka A. Formation of the monitoring system for non-production enterprises / A. Roskladka, N. Roskladka, V.Hamalii, N. Geseleva // Big Data processing: methods, models and information technologies. Shioda GmbH, Steyer, Austria, 2019. P. 188-215.
  8. Proniuk G., Geseleva N., Kyrychenko I., Tereshchenko G. Spatial Interpretation of the Notion of Relation and Its Application in the System of Artificial Intelligence [Електроннийресурс] / G. Proniuk, N. Geseleva, I. Kyrychenko, G. Tereshchenko // CEUR Workshop Proceedings of the 3rd International Conference on Computational Linguistics and Intelligent Systems (COLINS2019). Volume I: Main Conference, Kharkiv, Ukraine, April 18-19, 2019. – Режимдоступудоресурсу: http://ceur-ws.org/Vol-2362/paper24.pdf
  9. Кулаженко В. В. Нейромережеве моделювання процесу економічно безпеки підприємства / В. В. Кулаженко // Колективна наукова монографія «Проблеми та перспективи економічної кібернетики». – К.: ВД ТЗОВ «AgrarMediaGroup», 2013. – С. 226–231.
  10. Kulazhenko V. E-trade market analusis using data clustering methods. Big Data processing: methods, models and information technologies: monograph/Pursky O., Moroz I., Ivanova I., Kulazhenko V. – edited by Oleg I. Pursky. – Shioda GmbH, Steyr, Austria, 2019. – 90-161 pp.

Mathematical and computer modeling of digital economy processes 

Digital economy is a scientific field applying modern digital technologies to management of economic systems. In this area,  modeling, research and organization of management processes in economic systems are conducted with the use of modern information technology.