Overview

Victor Mykhailovych Sineglazov is a Ukrainian professor whose research covers hybrid neural networks, computer vision, control systems and computer-aided design. He is a professor in the Department of Artificial Intelligence at Igor Sikorsky Kyiv Polytechnic Institute and editor-in-chief of the journal Electronics and Control Systems.

He received the State Prize of Ukraine in Science and Technology in 2004 and the title of Honoured Worker of Science and Technology of Ukraine in 2009. He was included in the 2025 Elsevier–Stanford list of the world's top 2% scientists, based on citation indicators.

His books include textbooks in English and Spanish and the co-authored monograph Artificial Intelligence Systems Based on Hybrid Neural Networks: Theory and Applications (2021).

His Ukrainian name is Віктор Михайлович Синєглазов. His name also appears as Victor Sineglazov and Viktor Mykhailovych Syniehlazov.

Early life and education

Born in Odesa on 9 August 1950, Sineglazov graduated from Kyiv Polytechnic Institute in 1973. He studied automation and telemechanics in the Faculty of Automation and Electrical Instrument Engineering.

He earned the Candidate of Technical Sciences degree in 1980 and the Doctor of Technical Sciences degree in 1995. His Candidate dissertation, "Time-optimal and fuel-optimal control of non-stationary and stochastic systems", was defended on 21 January 1980. He defended his doctoral dissertation, "Information processing and control of spatially distributed mechanical and thermophysical processes", on 29 June 1995.

He received the academic titles of senior researcher in 1983, associate professor in 1991 and professor in 1995.

Academic career

Sineglazov began his career as an engineer in Kyiv Polytechnic Institute's Department of Technical Cybernetics, where he worked from 1973 to 1974. He undertook postgraduate study there from 1974 to 1977 and then worked as a senior researcher.

At the National Aviation University, he was an associate professor from 1989 to 1995 and later headed the Department of Aviation Computer-Integrated Complexes. From 2003 to 2010, he directed the university’s Institute of Electronics and Control Systems.

In 2026, his roles at Igor Sikorsky Kyiv Polytechnic Institute include professor in the Department of Artificial Intelligence and deputy director for international affairs of the Educational and Scientific Institute of Applied System Analysis.

Research

Sineglazov studies control and optimisation, neural network design and image analysis. His work applies these methods to aviation, renewable energy, environmental monitoring and medical imaging.

Control theory and engineering optimisation

His early work developed methods for time-optimal and fuel-optimal control of linear stochastic systems. He also proposed algorithms for placing sensors in systems whose behaviour varies across space and studied how to identify an aircraft's elastic and mass characteristics through vibration tests. His optimisation research includes adapting algorithms to problems with several objectives and constraints, and converting unconstrained optimisation problems into constrained ones.

Neural networks and semi-supervised learning

Sineglazov proposed methods for choosing neural network structures, training ensembles and propagating labels through datasets that contain both labelled and unlabelled examples. His 2021 monograph, co-authored with Michael Z. Zgurovsky and Elena Chumachenko, examines the formation and development of hybrid network architectures. He also developed methods for forming training datasets to optimise neural network tuning through semi-supervised learning. The National Academy of Sciences of Ukraine's report for 2023 identifies potential applications of this work in medicine and defence.

Computer vision and image restoration

His computer vision research includes proposed neural network methods for reconstructing higher-resolution imagery from unmanned aerial vehicles (UAVs) for navigation and restoring missing or damaged image regions. He developed compact models for detecting small and overlapping underwater objects on vehicles with limited computing resources. For transfer learning, he proposed distance measures between segmentation datasets to help select pretraining data and evaluated them on medical image datasets.

Time series forecasting and motion prediction

Sineglazov developed forecasting methods using neural network ensembles and hybrid approaches that combine neural networks with models constructed from data. Applications include airline passenger traffic. He also proposed recurrent neural models for time series forecasting and analysed their dynamical stability. For vehicle trajectory prediction, he used a modified transformer model and proposed a way to construct training data with several possible trajectories from examples containing a single observed trajectory.

UAV navigation and robotic systems

His work on UAV navigation examines the integration of inertial and satellite navigation. He proposed visual navigation methods that use landmarks with known coordinates to correct position estimates and developed a ground-testing system that places physical UAV equipment in a simulated flight environment. For agricultural UAVs, he proposed route-planning methods that account for field coverage, obstacles and energy requirements, including returning to recharge and then resuming a mission.

Renewable energy and solar-powered aviation

Sineglazov directed the National Aviation University's renewable energy centre, where wind turbines and rotating solar installations were developed. He proposed hybrid photovoltaic and wind power supplies for UAV control centres, alongside methods for selecting solar panels, batteries and diesel generators according to cost, fuel use and reliability. His work on solar-powered aviation includes a framework for conceptual aircraft design that combines models of aircraft performance, environmental conditions and energy supply.

Remote sensing and environmental monitoring

He proposed methods for detecting and classifying landmines from UAV hyperspectral imagery and radar measurements. The radar image classifier uses both labelled and unlabelled training data. He also developed a system that classifies bark-beetle damage using real and generated multispectral images. For hyperspectral image classification, he proposed generating labelled spectral samples to supplement limited training datasets and evaluated the method on benchmark datasets.

Medical imaging and diagnostic support

Sineglazov developed neural network methods for analysing computed tomography (CT) images and assessing tuberculosis activity. He was one of the developers of a tuberculosis diagnostic system presented publicly in October 2021. His research also includes proposed ensemble methods for segmenting heart-valve vegetations in echocardiography images. In 2026, he co-authored a study on predicting fractures in individual vertebrae from routine CT scans. The study evaluated the method at a single centre and identified external validation as a necessary next step.

Language processing and other applications

He proposed systems that combine facial images and speech to estimate emotional state, and systems that classify Norwegian documents using contextual language representations and generated training examples. He also developed an algorithm for selecting traffic-light phases to reduce delays, tested on a simplified road network. His 2021 monograph covers automated road management and fire surveillance as applications of hybrid neural networks.

Professional activities

Alongside his work as editor-in-chief of the journal Electronics and Control Systems, Sineglazov is on the editorial board of the American Journal of Neural Networks and Applications. He chairs the specialised doctoral dissertation council D 26.062.08, whose membership was approved by the Ministry of Education and Science of Ukraine in 2014.

He regularly chairs the organising committees of two recurring IEEE conferences: Methods and Systems of Navigation and Motion Control (MSNMC), and Actual Problems of Unmanned Aerial Vehicles Development (APUAVD). In 2024, he was also on the programme committee of the Computer Information Systems and Software Engineering conference at Lviv Polytechnic.

Sineglazov was a member of the organising committees for the All-Ukrainian Student Research Competition in Artificial Intelligence in 2024 and its international edition in 2025. The competition website lists him as chair of its computer vision section.

He is a Senior Member of the Institute of Electrical and Electronics Engineers (IEEE) and a member of its Aerospace and Electronic Systems Society and Computational Intelligence Society.

Honours

Sineglazov's entry in the single-year table of the 2025 Elsevier–Stanford citation database is based on citations received in 2024. It lists operations research as his primary subfield, with artificial intelligence and image processing as the second subfield.

His honours include:

  • Medal "For Diligent Work" (2001)
  • Certificate of Merit of the Ministry of Education and Science of Ukraine (2001)
  • Badge "Excellence in Education of Ukraine" (2002)
  • State Prize of Ukraine in Science and Technology (2004), for work on protecting aircraft from destructive and disruptive electromagnetic effects
  • Petro Mohyla badge of the Ministry of Education and Science of Ukraine (2007)
  • Honoured Worker of Science and Technology of Ukraine (2009)
  • M. K. Yangel badge (2010)
  • Certificate of Honour from the State Space Agency of Ukraine (2011 and 2026)
  • O. M. Makarov badge (2012)
  • Badge "For Scientific and Educational Achievements" of the Ministry of Education and Science of Ukraine (2022)