Areas of research

• Creation of new technologies and algorithms of artificial intelligence.
• Modeling of complex weakly structured processes and systems.
• Pattern recognition.
• NLP and LLM development.
• Forecasting in economy and finance.
• Modeling of economic and financial risks.

Scientific supervision of postgraduate and doctoral students

• Strelchenko, Inna Ilivna — DSc (Habil.) in Economics by the specialty Mathematical Methods, Models and Information Technologies in Economics; dissertation on the topic “Mathematical Modeling of Processes of Cross-Border Spread of Crisis Phenomena in Financial Markets”; Diploma DD No. 011454 dated 29.06.2021.
• Khokhlov, Valentyn Yuriyovych — DSc (Habil.) in Economics by the specialty Mathematical Methods, Models and Information Technologies in Economics; dissertation on the topic “Modeling of Securities Portfolios in Conditions of Global Economic Instability”; Diploma DD No. 007052 dated 16.05.2018.
• Ben, Vladyslav Petrovych — PhD in Economics by the specialty Mathematical Methods, Models and Information Technologies in Economics; dissertation on the topic “System of Models for Assessing the Creditworthiness of Individual Borrowers”; Diploma DK No. 055010 dated 16.12.2019.
• Kaidanovych, Dmytro Bronislavovych — PhD in Economics by the specialty Mathematical Methods, Models and Information Technologies in Economics; dissertation on the topic “Modeling of Economic Systems and Processes Using Backpropagation Neural Networks”; Diploma DK No. 013311 dated 25.04.2013.
• Olkhovska, Oksana Leonidivna — PhD in Economics by the specialty Mathematical Methods, Models and Information Technologies in Economics; dissertation on the topic “Modeling the Financial State of Insurance Company”; Diploma DK No. 004629 dated 17.02.2012.

Participation in international research and/or educational projects

• The head of the Ukrainian team in a joint project in a consortium with organizations from Sweden, Latvia and Armenia No. 00152/2024 dated 21.08.2024 “iResilience: Strengthening democratic practises and media literacy” within the framework of the SI Baltic Sea Neighbourhood Programme (2024-2025).
• Participation in the project "Increasing the capacity of the digital innovation hub of the Kyiv Academic University “Virtual center for Digital Innovation NOSC-UA DIH”" within the framework of the international cooperation program "Digital Transformation of SMEs in the Eastern Partnership Countries" with the financial support of the German government in cooperation with Deutsche Gesellschaft fur Internationale Zusammenarbeit GmbH (2024).
• Head of the project for the Summer School on the implementation of the Association Agreement between Ukraine and the EU for specialists from government agencies of Ukraine with the participation of EU representatives within the framework of the EU Project “Support to implementation of EU-Ukraine Association Agreement” through the mediation of GFA Consulting Group GmbH under contract No. 1 dated 08.06.2017 (2017).
• Head of projects for the development of training modules on econometric forecasting and training of specialists of the Westminster Foundation for Democracy (Great Britain) within the framework of contracts No. 1 dated 18.04.2016 and No. 2 dated 20.06.2016 (2016).
• Head of projects for retraining of military personnel within the framework of the NATO-Ukraine program according to contracts with NATO Headquarters (Belgium) No. 2014\2369 dated 28.11.2014, No. 3097\2015 dated 06.08.2015, No. 26057 dated 12.02.2018 (2014-2021).

Profiles in international scientometric databases

• Scopus ID: 56011088600
• Web of Science Researcher ID: O-8856-2018
• ORCID ID: 0000-0002-8911-5677
• DBLP: 249/5089
• Google Scholar: MbbkRj8AAAAJ
• Semantic Scholar: 145460593
• Scientists of Ukraine (Vernadsky National Library of Ukraine) ID: 0015185

Total number of publications: more than 160 scientific and educational works

Key monographs:

• Soloviev, V., Bielinskyi, A., & Matviychuk, A. (2024). Crisis Phenomena Monitoring and Prevention in Complex Socio-Economic Systems. Publisher Tretyakov O.M. https://elibrary.kdpu.edu.ua/handle/123456789/10938

• Matviychuk, A. (2011). Artificial Intelligence in Economics: Neural Networks, Fuzzy Logic. KNEU.
• Matviychuk, A. (2007). Modeling of Economic Processes Using Fuzzy Logic Methods. KNEU.
• Matviychuk, A. (2005). Economic Risks in Investment Activities. UNIVERSUM-Vinnytsia.
• Matviychuk, A. (2005). Analysis and Forecasting of the Development of Financial and Economic Systems Using the Theory of Fuzzy Logic. Center for Educational Literature.
• Moroz, O., & Matviychuk, A. (2003). Optimal Management of Economic Systems Under Conditions of Uncertainty and Risk. UNIVERSUM-Vinnytsia.

Publications in scientific journals included in the scientometric database Scopus:

• Matviychuk, A., Zhytkevych, O., & Osadcha, N. (2024). Modeling carbon dioxide emissions reduction. Energy Reports, 12, 1876-1887. https://doi.org/10.1016/j.egyr.2024.08.004 (Scopus).
• Matviychuk, A., Derbentsev, V., Bezkorovainyi, V., Kmytiuk, T., & Hostryk, A. (2024). Leveraging Artificial Intelligence and Large Language Models for Fake Content Detection in Digital Media. CEUR Workshop Proceedings, 3933, 75-92. https://ceur-ws.org/Vol-3933/Paper_7.pdf (Scopus)
• Bielinskyi, A., Soloviev, V., Matviychuk, A., Solovieva, V., Kmytiuk, T., Velykoivanenko, H., & Tuzhykov, A. (2024). Modeling and Identifying States of Irreversibility in Energy-Related Markets. In E. Faure, Y. Tryus, T. Vartiainen, O. Danchenko, M. Bondarenko, C. Bazilo, & G. Zaspa (Eds.), Lecture Notes on Data Engineering and Communications Technologies: Vol. 221. Information Technology for Education, Science, and Technics (ITEST 2024) (pp. 243–256). Springer, Cham. https://doi.org/10.1007/978-3-031-71801-4_18 (Scopus).
• Bielinskyi, A., Soloviev, V., Solovieva, V., Matviychuk, A., Hushko, S., & Velykoivanenko, H. (2023). Stock Market Crashes as Phase Transitions. In G. Antoniou, V. Ermolayev, V. Kobets, V. Liubchenko, H. C. Mayr, A. Spivakovsky, V. Yakovyna, & G. Zholtkevych (Eds.), Communications in Computer and Information Science: Vol. 1980. Information and Communication Technologies in Education, Research, and Industrial Applications (pp. 203–214). Springer, Cham. https://doi.org/10.1007/978-3-031-48325-7_15 (Scopus).
• Zhytkevych, O., Matviychuk, A., & Kmytiuk, T. (2023). Modeling Nations’ Decarbonisation Potential. In F.Ortiz-Rodríguez, S. Tiwari, P. Usoro Usip, & R. Palma (Eds.), Communications in Computer and Information Science: Vol. 1888. Electronic Governance with Emerging Technologies (pp. 60-77). Springer. https://doi.org/10.1007/978-3-031-43940-7_6 (Scopus).
• Lukianenko, D., Matviychuk, A., Lukianenko, L., & Dvornyk, I. (2023). University competitiveness in the knowledge economy: a Kohonen map approach. CEUR Workshop Proceedings, 3465, 236–250. https://ceur-ws.org/Vol-3465/paper23.pdf (Scopus).
• Bielinskyi, A., Soloviev, V., Hushko, S., Kiv, A., & Matviychuk, A. (2023). High-order network analysis for financial crash identification. CEUR Workshop Proceedings, 3465, 132–149. https://ceur-ws.org/Vol-3465/paper15.pdf (Scopus).
• Derbentsev, V., Bezkorovainyi, V., Matviychuk, A., Pomazun, O., Hrabariev, A., & Hostryk, A. (2023). A comparative study of deep learning models for sentiment analysis of social media texts. CEUR Workshop Proceedings, 3465, 168–188. https://ceur-ws.org/Vol-3465/paper18.pdf (Scopus).
• Bielinskyi, A., Soloviev, V., Solovieva, V., Matviychuk, A., & Semerikov, S. (2023). The Analysis of Multifractal Cross-Correlation Connectedness Between Bitcoin and the Stock Market. In E. Faure, O. Danchenko, M. Bondarenko, Y. Tryus, C. Bazilo, & G. Zaspa (Eds.), Lecture Notes on Data Engineering and Communications Technologies: Vol 178. Information Technology for Education, Science, and Technics (pp. 323–345). Springer, Cham. https://doi.org/10.1007/978-3-031-35467-0_21 (Scopus).
• Bielinskyi, A.O., Matviychuk, A.V., Serdyuk, O.A., Semerikov, S.O., Solovieva, V.V., & Soloviev, V.N. (2022). Correlational and Non-extensive Nature of Carbon Dioxide Pricing Market. In O. Ignatenko, V. Kharchenko, V. Kobets, et al. (Eds.), Communications in Computer and Information Science: Vol. 1635. ICTERI 2021 Workshops (pp. 183–199). Springer. https://doi.org/10.1007/978-3-031-14841-5_12 (Scopus).
• Bielinskyi, A. O., Khvostina, I., Matviychuk, A., Semerikov, S., Serdyuk, O., Solovieva, V., & Soloviev, V. N. (2021). Predictors of oil shocks. Econophysical approach in environmental science. IOP Conference Series: Earth and Environmental Science, 628(1), Article 012019. https://doi.org/10.1088/1755-1315/628/1/012019 (Scopus).
• Kiv, A, Soloviev, V. N., Semerikov, S., Danylchuk, H., Kibalnyk, L., Matviychuk, A., & Striuk, A. (2021). Machine learning for prediction of emergent economy. CEUR Workshop Proceedings, 3048, I–XXXI. http://ceur-ws.org/Vol-3048/paper00.pdf (Scopus).
• Bielinskyi, A., Hushko, S., Matviychuk, A., Serdyuk, O., Semerikov, S., & Soloviev, V. N. (2021). Irreversibility of financial time series: a case of crisis. CEUR Workshop Proceedings, 3048, 134–150. http://ceur-ws.org/Vol-3048/paper04.pdf (Scopus).
• Derbentsev, V., Matviychuk, A., & Soloviev, V.N. (2020). Forecasting of Cryptocurrency Prices Using Machine Learning. In L. Pichl, C. Eom, E. Scalas, & T. Kaizoji (Eds.), Advanced Studies of Financial Technologies and Cryptocurrency Markets (pp. 211-231). Springer. https://doi.org/10.1007/978-981-15-4498-9_12 (Scopus).
• Derbentsev, V., Matviychuk, A., Datsenko, N., Bezkorovainyi, V., & Azaryan, A. (2020). Machine learning approaches for financial time series forecasting. CEUR Workshop Proceedings, 2713, 434-450. http://ceur-ws.org/Vol-2713/paper47.pdf (Scopus).
• Matviychuk, A., Lukianenko, O., & Miroshnychenko, I. (2019). Neuro-fuzzy model of country's investment potential assessment. Fuzzy economic review, 24(2), 65-88. https://doi.org/10.25102/fer.2019.02.04 (Scopus).
• Matviychuk, A., Novoseletskyy, O., Vashchaiev, S., Velykoivanenko, H., & Zubenko, I. (2019). Fractal analysis of the economic sustainability of industrial enterprise. CEUR Workshop Proceedings, 2422, 455-466. http://ceur-ws.org/Vol-2422/paper37.pdf. (Scopus).
• Kiv, A., Semerikov, S., Soloviev, V., Kibalnyk, L., Danylchuk, H., & Matviychuk, A. (2019). Experimental Economics and Machine Learning for Prediction of Emergent Economy Dynamics. CEUR Workshop Proceedings, 2422, 1-4. http://ceur-ws.org/Vol-2422/paper00.pdf (Scopus).
• Matviychuk, A., Strelchenko, I., Vashchaiev, S., & Velykoivanenko, H. (2019). Simulation of the Crisis Contagion Process Between Countries with Different Levels of Socio-Economic Development. CEUR Workshop Proceedings, 2393, 485-496. http://ceur-ws.org/Vol-2393/paper_423.pdf (Scopus).
• Matviychuk, A., & Velykoivanenko, H. (2014). Modeling of tax incentives effectiveness. Economic Annals-XXI, 5-6, 105-108. http://soskin.info/userfiles/file/2014/5-6_2014/Matviychuk_Velykoivanenko.pdf (Scopus).
• Matviychuk, A. (2010). Bankruptcy prediction in transformational economy: discriminant and fuzzy logic approaches. Fuzzy economic review, 15(1), 21-38. https://doi.org/10.25102/fer.2010.01.02 (Scopus).
• Matviychuk, A. (2006). Fuzzy logic approach to identification and forecasting of financial time series using Elliott wave theory. Fuzzy economic review, 11(2), 51-68. https://doi.org/10.25102/fer.2006.02.04 (Scopus).