Scientific and pedagogical staff

2024 – Associate Professor of Higher Education Institution, Department of Theoretical and Applied Informatics

2021 – Obtained the scientific degree of Candidate of Technical Sciences, V. N. Karazin Kharkiv National University

2013 – obtained specialist (master's) qualification – National Aerospace University named after N.E. Zhukovsky «Kharkiv Aviation Institute»

Research Areas

Artificial Intelligence
Statistics
Applied Mathematics
Information Systems
Medical Informatics

Links to pages on academic networks:

Lecture courses for bachelor's students

  • Architecture of Computing Systems
  • Software Design
  • Modern Java Technologies 

Lecture courses for master's students:

  • Fundamentals of Quantum Computing and Quantum Informatics

Educational and Scientific Projects

Leading Researcher, research project in 2023-2025 (joint conduct of fundamental new research in the field of demography and computer science) between Max-Planck-Gesellschaft zur Förderung der Wissenschaften e.V and National Aerospace University named after N.E. Zhukovsky «Kharkiv Aviation Institute», Department of Mathematical Modeling and Artificial Intelligence.

Project Manager at V. N. Karazin Kharkiv National University of the German Academic Exchange Service (DAAD). Project title «Further development of bachelor's/master's double degree programs in mathematics and computer science between Ulm University and V. N. Karazin Kharkiv National University», «German-Ukrainian University Network 2025-2029».

Professional activity (participation in associations):

Participation in the professional association Computer Vision Foundation (a non-profit organization that fosters and supports research in all aspects of computer vision)

Member of the international scientific organization ISSMO – International Society for Structural and Multidisciplinary Optimization (ISSMO Member Number 32722).

  1. Butkevych M., Meniailov I., Lutsiv Y., Kraivskyi B., Chumachenko D. WAR-DRIVEN DISPLACEMENT AND COVID-19 IN POLAND: SIMULATION STUDY USING LSTM MODEL [WAR-DRIVEN POPULATION DISPLACEMENT AND COVID-19 IN POLAND: SIMULATION USING LSTM MODEL] (2025) Radioelectronic and Computer Systems, 2025 (4), pp. 25 – 34. DOI: 10.32620/reks.2025.4.02
  2. Parfeniuk Y., Bazilevych K., Meniailov I., Chumachenko D. A MULTI-LAYER DELTA LAKEHOUSE FOR EPIDEMIOLOGICAL MONITORING AND FORECASTING UNDER EMERGENCIES (2025) Advanced Information Systems, 9 (4), pp. 57 – 65. DOI: 10.20998/2522-9052.2025.4.08
  3. Rukkas K., Morozova A., Meniailov I., Momot M. BUFFER BASED ON TRAFFIC FRACTALITY [ANALYSIS OF PACKET LOSS PROBABILITY MODELS IN A ROUTER BUFFER CONSIDERING TRAFFIC FRACTALITY]. (2025) Radioelectronic and Computer Systems, 2025 (3), pp. 245 – 256. DOI: 10.32620/reks.2025.3.17
  4. Chumachenko D., Bazilevych K., Butkevych M., Meniailov I., Parfeniuk Y., Sidenko I., Chumachenko T. METHODOLOGY FOR ASSESSING THE IMPACT OF EMERGENCIES ON THE SPREAD OF INFECTIOUS DISEASES (2024) Radioelectronic and Computer Systems, 2024 (3(111)), pp. 6 – 26. DOI: 10.32620/REKS.2024.3.01
  5. Krivtsov S., Parfeniuk Y., Bazilevych K., Meniailov I., Chumachenko D. PERFORMANCE EVALUATION OF PYTHON LIBRARIES FOR MULTITHREADING DATA PROCESSING. (2024) Advanced Information Systems, 8 (1), pp. 37 – 47. DOI: 10.20998/2522-9052.2024.1.05
  6. Bazilevych K.O., Kyrylenko O.Yu., Parfeniuk Y.L., Yakovlev S.V., Krivtsov S.O., Meniailov I.S., Kuznietcova V.O., Chumachenko D.I. INFORMATION SYSTEM FOR ASSESSING THE INFORMATIVENESS OF AN EPIDEMIC PROCESS FEATURES (2023) System Research and Information Technologies, 2023 (4), pp. 100 – 112. DOI: 10.20535/SRIT.2308-8893.2023.4.08
  7. Alekseeva V., Nechyporenko A., Frohme M., Gargin V., Meniailov I., Chumachenko D. Intelligent Decision Support System for Differential Diagnosis of Chronic Odontogenic Rhinosinusitis Based on U-Net Segmentation (2023) Electronics (Switzerland), 12 (5), art. no. 1202. DOI: 10.3390/electronics12051202
  8. Bazilevych K., Kyrylenko O., Parfenyuk Y., Krivtsov S., Meniailov I., Kuznietcova V., Chumachenko D. COMPARATIVE ANALYSIS OF THE MACHINE LEARNING MODELS DETERMINING COVID-19 PATIENT RISK LEVELS [COMPARATIVE ANALYSIS OF MACHINE LEARNING MODELS FOR DETERMINING COVID-19 PATIENT RISK LEVELS] (2023) Radioelectronic and Computer Systems, (3(107)), pp. 5 – 17. DOI: 10.32620/reks.2023.3.01
 
  1. Chumachenko, Ie. Meniailov, K. Bazilevych, Yu. Parfeniuk, T. Chumachenko, Integrating Epidemic Simulation into Crisis Management Programs: Lessons from Ukraine, in Innovative Technologies for Project and Program Management: Collective monograph edited by I. Linde. European University Press. Riga: ISMA, 2025. pp. 71-83. doi: https://doi.org/10.30837/MMP.2025.071 (chapter of a collective monograph).
  2. Bazilevych K., Kyrylenko O., Parfeniuk Y., Meniailov I. Emerging Technologies in Infectious Disease Surveillance and Control: Current Solutions and Future Directions. (2025) Lecture Notes in Networks and Systems, 1473 LNNS, pp. 196 – 207. DOI: 10.1007/978-3-031-94845-9_17 (chapter of a collective monograph).
  3. Chumachenko D., Chumachenko T., Meniailov I., Muradyan O., Zholtkevych G. Forecasting of COVID-19 Epidemic Process in Ukraine and Neighboring Countries by Gradient Boosting Method (2023) Lecture Notes on Data Engineering and Communications Technologies, 178, pp. 503 – 514. DOI: 10.1007/978-3-031-35467-0_30 (chapter of a collective monograph).
  4. Meniailov I., Krivtsov S., Chumachenko T. Dimensionality Reduction of Diabetes Mellitus Patient Data Using the T-Distributed Stochastic Neighbor Embedding (2023) Lecture Notes in Networks and Systems, 536 LNNS, pp. 86 – 95. DOI: 10.1007/978-3-031-20141-7_9 (chapter of a collective monograph).
  1. Panchenko A., Yarkin D., Frolov V., Meniailov I., Vladymyrova M., Kuznietcova V. Investigation of Machine Learning Techniques for Restoring the Quality of Compressed Audio (2025) CEUR Workshop Proceedings, 4164, pp. 66 – 76.
  2. Parfeniuk Y., Kurinniy D., Bazilevych K., Meniailov I. Using Machine Learning Methods to Analyze HIV Incidence in Ukraine. (2025) CEUR Workshop Proceedings, 4164, pp. 427 – 439.
  3. Butkevych M., Meniailov I., Bazilevych K., Parfeniuk Y., Chumachenko D. Simulation of influenza dynamics with LSTM deep learning model (2024) CEUR Workshop Proceedings, 3892, pp. 115 – 125.
  4. Morozova A., Bielova L., Meniailov I. Approaches to Organization of Change Tables for Real-Time Business Intelligence. (2023) CEUR Workshop Proceedings, 3641, pp. 96 – 106.
  5. Meniailov I., Krivtsov S., Chumachenko T. Dimensionality Reduction of Diabetes Mellitus Patient Data Using the T-Distributed Stochastic Neighbor Embedding. (2023) Lecture Notes in Networks and Systems, 536 LNNS, pp. 86 – 95. DOI: 10.1007/978-3-031-20141-7_9.
  6. Chumachenko D., Chomko V., Meniailov I., Krivtsov S., Padalko H. Estimation of Ukrainian Refugees Impact on COVID-19 Dynamics in Czech Republic using Prophet Model. (2023) CEUR Workshop Proceedings, 3641, pp. 15 – 25.
  7. Chumachenko D., Chomko V., Meniailov I., Krivtsov S., Padalko H. A Data-Driven Simulation of Ukrainian Refugee Flows Impact on COVID-19 Dynamics in the UK. (2023) CEUR Workshop Proceedings, 3609, pp. 92 – 102.
  8. Meniailov I. Architecture of bank of epidemic models, Proceedings of the V International Scientific and Practical Conference of IT Professionals and Computer Systems Analysts «ProfIT Conference», 2023, Pp. 26-27.

Meniailov Yevhen Serhiiovych

acting dean of the faculty, Candidate of Technical Sciences, associate professor of the HEI of the Department of Theoretical and Applied Informatics