Scientific Research and Projects

Research Areas of the Department

Scientific research and development at the Department of CMDA, in line with the focus of the educational program “Intelligent Data Analysis”, are carried out in the following thematic areas:

  • Methods of intelligent data analysis and forecasting based on machine learning:
      •  Intelligent decision-making systems using methods of Preference Learning and Ranking Learning
      • Predictive analytics of nonlinear time series.
      • Methods for constructing composite indicators based on kernel machine learning techniques;
      • Semi-supervised learning with “partial teacher involvement” on aggregated data
  • Mathematical and computer modeling of technical, financial-economic systems and information processes:
      • Interval models of aggregated Markov systems
      • Optical diagnostic systems with artificial intelligence.
      • Modeling of non-contact surface diagnostics processes;
  • Information technologies for managing network and multi-agent systems under uncertainty and risk:
    • Consensus control of multi-agent systems;
    • Management of logistics systems and supply chains.

The Most Significant Scientific Results Obtained

  • New methods of robust consensus control of networked multi-agent systems under uncertainty with respect to disturbances, delays and network topology have been developed based on the method of invariant ellipsoids and linear matrix inequalities.
  • New methods have been designed for constructing nonlinear models of composite indicators, preference functions and ranking functions from aggregated expert-statistical data, using kernel-based semi-automatic machine learning methods on clusters in the feature space.
  • Methods have been developed for constructing and analyzing aggregated mathematical models of discrete stochastic systems with interval uncertainty models.
  • New methods and information technologies for automated intelligent optical diagnostics have been created, employing machine learning techniques.

Scientific and Technical Projects Completed (over the last 10 years)

  • Funded by the Ministry of Education and Science of Ukraine (state budget):
  1. Development of an information technology for forming national-level project portfolios based on a simulation model of scientific and technological development of Ukraine, 2015-2018.
  2. Development of methods for solving inverse problems of diagnostics and control of nonlinear systems using synergetics and computational intelligence, 2011-2014.
  3. Development of statistical and neural network methods and information technologies for computer monitoring of complex systems under uncertainty, 2010-2013.
  • Funded by business contracts and agreements:
  1. Project under contract: “Semi-supervised machine learning algorithms” («Алгоритми автоматизованого (напівавтоматичного) машинного навчання»). Client – Samsung Electronics Ukraine Company LTD, Contract RD/640-14-0313 (No. 99371) dated 15.03.2013.
  2. Project under contract: “Semi-supervised clusterization of large corpora of short texts” («Автоматизована (напівавтоматична) кластеризація великої кількості об’єктів за обмеженим текстовим описом»). Client – Samsung Electronics Ukraine Company LTD, Contract RD/482/06-1112 dated 01.11.2012.
  3. Project under contract: “Development of adaptive models for ranking sites in search engines based on ranking learning.” Client – Noosphere Ventures & TrafficDNA.com, UK.
  4. Project under contract: “Development of a WEB-based decision support system for trading on the electronic stock market.” Client – Math+.com & Tradespoon.com, USA.
  5. Contract No. 99658 (01.01.2010 – 30.11.2014): “Modeling of the energy systems of the Republic of Tajikistan.” Client – OJSC “Barki Tojik”, Republic of Tajikistan.

Scientific Publications of the Department’s Staff (over the last 10 years)

Over the past decade, the department’s staff have published more than 80 scientific works (monographs/chapters of monographs, articles in periodicals and conference papers in printed proceedings), indexed in the Scopus and Web of Science databases. The total h-index of the department’s staff, according to Scopus, is 24.

Monographs / Book Chapters

  • Lyubchyk L.M., Dorofieiev Yu.I. Information Technologies for Inventory Management in Supply Networks (Monograph). Kharkiv, NTU “KhPI”, 2019. 186 p.
  • Lyubchyk L.M., Kostiuk O.V. Selective-Invariant Control of Multidimensional Systems. Dynamic Disturbance Observers (Monograph). LAP LAMBERT Academic Publishing GmbH & Co. KG, Saarbrücken, Germany, 2013. 147 p.
  • Lyubchyk L.M. Optimal Information Fusion in Stochastic Unknown Input Observer network. Book Chapter in: V. Haasz and K. Madani (Eds.), Advanced Data Acquisition and Intelligent Data Processing, River Publishers. 2014. pp. 127-158. 
  • Lyubchyk L.M., Grinberg G.L. Preference Function Reconstruction for Multiple Criteria Decision Making Based on Machine Learning Approach. Book Chapter in L. A. Zadeh et al. (Eds.). Recent Developments and New Directions in Soft Computing. Springer, Switzerland, 2014. pp. 53-63. 
  • Lyubchyk L. M., Yu.I. Dorofieiev. Robust decentralized inventory control in large-scale supply networks. Book Chapter in Information and Computer Technology, Modeling and Control. Pisa Publishing, USA, 2017. 
  • Lyubchyk L. M., Yu.I. Dorofieiev. Decentralized guaranteed cost inventory 6 control of supply networks with uncertain delays. Book Chapter in V. M. Kuntsevich et al. (Eds). Control systems: theory and applications Denmark: River Publishers, 2018. Pp. 65-95. 
  • Lyubchyk L. M., Grinberg G.L., Galuza A.A., Semi-supervised Learning to Rank with Nonlinear Preference Model. Book Chapter in Book Series: Studies in Fuzziness and Soft Computing, J. Kacprzyk (ed.), Springer, 2020. 
  • Lyubchyk L.M. Inverse Model Approach to Disturbance Rejection Problem // Book Chapter in V. M. Kuntsevich et al. (Eds.). Advanced Control Systems: Theory and Applications. River Publishers. 2021.

Articles in Periodicals and Proceedings of International Conferences

More details available at the link: Publications of the Department’s Staff, 2010-2024.

Participation in Scientific Conferences

The faculty members of the department regularly present research papers at prestigious international scientific conferences both in Ukraine and abroad, in particular:

  • ІЕЕЕ International Conference Data Stream Mining & Processing (DSMP’2016, DSMP’2018 DSMP’2020), http://www.dsmp.in.ua/;
  • ІЕЕЕ International Conference on Advanced Computer Information Technologies (ACIT’2019, ACIT’2020, ACIT’2023), https://acit.wunu.edu.ua/;
  • IEEE International Conference on System Analysis & Intelligent Computing (SAIC’2018, SAIC’2020, SAIC’2022),

http://saic.ieee.org.ua/?page_id=96;

  • IEEE International Conference on Dependable Systems, Services and Technologies, Athens, Greece (DESSERT 2022, DESSERT 2023,

https://www.dessert-conf.org/dessert-2023/

In 2023, the department’s faculty members Prof. L.M. Lyubchyk and Assoc. Prof. K.S. Yamkovyi received the award for the best presentation at the international conference “2023 IEEE 12th International Conference on Intelligent Data Acquisition and Advanced Computing Systems: Technology and Applications (IDAACS)”, Dortmund, Germany, 2023.

As part of the attestation process for second-cycle higher education students (Master’s degree), the approbation of research results of the final qualification thesis at a scientific conference with the publication of conference abstracts is mandatory. In particular, this requirement is fulfilled through participation in the International Scientific and Practical Conference “Information Technology: Science, Engineering, Technology, Education, Health. MicroCAD” (https://lessons.gilect.net/site01/microcad/).

SECTION 9. COMPUTER SCIENCE AND INFORMATION TECHNOLOGY

Subsection 9.2 – Computer and Mathematical Modeling. Systems Analysis and Project Management

MicroCAD-2023 Conference PROGRAM

MicroCAD-2023 Book of Abstracts