Hybrid systems of artificial intelligence, machine learning, deep learning, data mining, and data analytics.

• Distributed information and analytical systems (cybsec)
• Security in Cloud Technologies and Big Data

More than 200 publications (among 4 monographs in Ukraine, 7 book chapters, 1  tutorial), 2 patents for utility model.

Main publication:

• Vlasenko A., Vlasenko N., Vynokurova O., Peleshko D. An Empirical Mode Decomposition Based Method to Synthesize Ensemble Multidimensional Gaussian Neuro-Fuzzy Models in Financial Forecasting // In: Babichev S., Peleshko D., Vynokurova O. (eds) Data Stream Mining & Processing. DSMP 2020. Communications in Computer and Information Science, vol 1158. P. 140-149 Springer, Cham.
• Vynokurova O., Peleshko D., Peleshko M. Hybrid Deep Convolutional Neural Network with Multimodal Fusion // In: Babichev S., Peleshko D., Vynokurova O. (eds) Data Stream Mining & Processing. DSMP 2020. Communications in Computer and Information Science, vol 1158. P 62-78 Springer, Cham.
• Vynokurova, O., Peleshko, D., Zhernova, P., Perova, I., Kovalenko, A. Solving fraud detection tasks based on wavelet-neuro autoencoder // Advances in Intelligent Systems and Computing, 2021, 1246 AISC, P. 535-546
• Vlasenko, A., Rashkevych, Y., Vlasenko, N., Peleshko, D., Vynokurova, O. A hybrid EMD – Neuro-fuzzy model for financial time series analysis // Proc. of the 2020 IEEE 3rd International Conference on Data Stream Mining and Processing, DSMP 2020, 2020, pp. 112–115.
• Vynokurova, O., Peleshko, D. Hybrid multidimensional deep convolutional neural network for multimodal fusion // Proc. of the 2020 IEEE 3rd International Conference on Data Stream Mining and Processing, DSMP 2020, 2020, pp. 131–135
• Peleshko, D., Vynokurova, O., Oskerko, S., Maksymiv, O., at all Real-Time Flame Detection Using Hypotheses Generating Techniques // Advances in Intelligent Systems and Computing, 2020, 938, pp. 172–182
• Vlasenko, A., Vlasenko, N., Vynokurova, O., Bodyanskiy, Y., Peleshko, D. A novel ensemble neuro-fuzzy model for financial time series forecasting // Data, 2019, 4(3), 126
• Bodyanskiy, Y., Dolotov, A., Peleshko, D., Rashkevych, Y., Vynokurova, O. Online time series changes detection based on neuro-fuzzy approach // Predictive Maintenance in Dynamic Systems: Advanced Methods, Decision Support Tools and Real-World Applications, 2019, pp. 131–166
• Bodyanskiy, Y., Dolotov, A., Peleshko, D., Rashkevych, Y., Vynokurova, O. Associative probabilistic Neuro-Fuzzy system for data classification under short training set conditions // Advances in Intelligent Systems and Computing, 2019, 761, pp. 56–63

Education

2002 – Engineer in Computer Systems, NURE, specialty – Intelligent Integrated Systems.

2005 – Ph.D., specialty – 05.13.23 Systems and Means of Artificial Intelligence.

2005 – Senior Researcher, specialty – 05.13.23 Systems and Means of Artificial Intelligence.

2012 – Dr.Sc., specialty – 05.13.23 Systems and Means of Artificial Intelligence.

2014 – Professor in Cybersecurity.

Academic Work

2004-2005 – Assistant Professor of Artificial Intelligence Department, NURE.

2004-2005 – Assistant Professor of Security of Information Technology Department, NURE.

2007-2013– Associate Professor of Security of Information Technology Department, NURE.

2013 -2017 –Professor of Security of Information Technology Department, NURE.

2005-2014 – Research Scientist, Senior Research Scientist, Lead Research Scientist of CSRL, NURE.

2013 р. – Visiting Research Scientist, Leibniz Universität Hannover, Germany

2017-2019 – professor, IT STEP University, Lviv, Ukraine.

2014 – present – Principal Research Scientist of CSRL, NURE.

2022 – present – професор кафедри кібербезпеки, Львівський національний університет ім. Івана Франка

Work at IT Companies

2018-2019 – Senior Professional, Samsung R&D Institute Ukraine (SRK), Kyiv, Ukraine

2019-2021 – Data Science Lead, Data Scientist / Machine Learning Engineer, GeoComply, Vancouver, Canada

2021 – present – Machine Learning R&D Scientist, Adoriasoft, Primex Lab

1st semester
2nd semester