جست‌وجوی استاد و پژوهشگر

Иван Симеонов Симеоновمشاهده پروفایل

دانشیار

• Computer Systems Design
• Ultrasonic Technology
• Image Processing
• +۳ مورد دیگر

Иван Симеонов Симеонов is an Associate Professor at Technical University Gabrovo specializing in Computer Systems and Networks. He holds a PhD in Computer Science (2006) and has extensive experience in ultrasonic sensor technology, embedded systems, and automated manufacturing. His career spans roles from researcher to academic leadership in technical fields. Key research focuses include non-contact ultrasonic material analysis, sensor design, and computer-aided engineering solutions. Education: Graduated from VMÉI (Gabrovo) in Electronic Technology, earned PhD in 2006 with thesis on computerized measurement systems. Fluent in English, German, and Russian with strong technical communication skills. Research interests emphasize interdisciplinary applications of computer systems in engineering contexts. His work bridges hardware design (e.g., programmable logic circuits) with software solutions (image processing algorithms). Notable projects include intelligent ultrasonic sensors for industrial automation and non-destructive material testing systems. Publications span 11 peer-reviewed articles and 68 conference presentations, focusing on ultrasonic technologies and embedded systems. Active member of ACM, Bulgarian Union of Automation and Informatics, and academic computer systems communities. Led over 15 research projects funded by national and EU programs, including EU's Erasmus initiatives for education innovation in computing.

Stephan Ivanov Ivanovمشاهده پروفایل

استاد

• Microcontrollers
• Programmable logic devices
• Sensor systems
• +۷ مورد دیگر

Professor Stephan Ivanov Ivanov serves as Head of the Department of Automation, Information and Control Technology within the Faculty of Electrical Engineering and Electronics at Technical University - Gabrovo. With a Doctorate in Technical Sciences, he has established himself as a leading researcher in sensor systems and industrial automation. His academic career spans over two decades with continuous contributions to both theoretical and applied research. Dr. Ivanov's research focuses on the intersection of microcontroller technology, programmable logic devices, and sensor systems. His work particularly emphasizes humidity and gas sensors, electronic nose technology, and the application of artificial neural networks in fire detection and food quality assessment. A significant portion of his recent research explores the innovative use of acoustic waves combined with deep learning for firefighting applications, representing a cutting-edge interdisciplinary approach. His publication record demonstrates consistent scholarly output, with 86 publications including books, conference papers, and journal articles. The most recent works (2022-2025) show a clear trend toward integrating deep neural networks with physical sensor systems, particularly in fire detection and environmental monitoring. His research bridges theoretical computer science with practical engineering applications, resulting in numerous international collaborations. As an educator and mentor, Professor Ivanov has supervised five PhD students, with three currently active in their research. His leadership extends to coordinating multiple international projects focused on incorporating 3D design and programming into educational curricula. His work demonstrates a commitment to both advancing scientific knowledge and applying it to practical educational and industrial challenges.

Dragomir Penkov Chantovمشاهده پروفایل

دانشیار

• Chaos Theory
• Control Theory
• Secure Data Transmission
• +۳ مورد دیگر

Dragomir Penkov Chantov is an Associate Professor at the Technical University of Gabrovo, Bulgaria, where he works in the Department of Automation, Information and Control Technology within the Faculty of Electrical Engineering and Electronics. Holding a Doctorate in Technical Sciences, he has been a faculty member since 1998, specializing in Theory of Automatic Control. His academic career includes significant contributions to chaos theory and control systems. Chantov's primary research interests focus on Chaos Theory and Control Theory, with particular emphasis on chaotic synchronization methods, secure data transmission systems, and nonlinear control applications. His work bridges theoretical mathematics with practical engineering applications, especially in cybersecurity and industrial control systems. He has developed numerous synchronization schemes including identical, anti-, hybrid, scaled, and oscillating synchronization techniques for various chaotic systems. His research output shows a clear progression from fundamental chaotic system analysis toward practical applications in secure communications and industrial cybersecurity. The publications demonstrate expertise in both theoretical aspects (Lyapunov stability, hyperchaotic systems) and applied implementations (data encryption, image transmission security). His recent work has increasingly focused on multi-system synchronization and industrial cybersecurity applications within Industry 4.0 frameworks. Electronic voting systems at Technical University - Gabrovo (2022) Security methods for cyber-physical systems in Industry 4.0 (2020) Schools for Makers: Incorporating 3D design into secondary education (2020) Smart drug dispensary with personal information protection (2017) Chantov has supervised at least one PhD student, Christina Svetoslavova Stoycheva, whose dissertation focused on the synthesis and analysis of chaotic synchronization systems. His teaching portfolio includes Systems Theory, Control Theory (I & II), System Identification, Microprocessor Technology, and Control of Renewable Energy Sources. His international collaborations and specializations at institutions in Germany, Czech Republic, and Austria have enriched his research perspective.

STANIMIR YORDANOV YORDANOVمشاهده پروفایل

دانشیار

• Automated Control Systems
• Intelligent Systems
• Industrial Systems Management
• +۶ مورد دیگر

Stanimir Yordanov Yordanov is an Associate Professor at the Department of Automation, Information and Control Technology within the Faculty of Electrical Engineering and Electronics at Technical University - Gabrovo. With a Doctorate in Technical Sciences and over 30 years of professional experience since 1993, he has established himself as a leading researcher and educator in control systems and automation. His educational background includes a Master of Engineering from VMEI - Gabrovo (1992) with specializations in Computer Engineering, Management Technologies, and Pedagogy, followed by a Doctorate (2006) and Associate Professor qualification (2010) in specialized technical fields. His teaching portfolio encompasses System Programming, Operating Systems, Digital Control Systems, and Industrial Robotics, among others. Professor Yordanov's research focuses on automated control systems, intelligent management of technological processes, industrial system monitoring, and object/system modeling. His work demonstrates a consistent trajectory toward increasingly sophisticated control algorithms and applications across diverse domains from electrohydraulic systems to environmental monitoring. The recent publications reveal a strong emphasis on advanced control techniques including neuro-PID regulators, model predictive control, and applications of artificial intelligence in industrial contexts. His extensive project portfolio includes 22 significant research initiatives, ranging from national projects like the 'Competence Center for Intelligent Mechatronic Systems' to international collaborations such as the 'MechMate' project focused on European SME growth. These projects demonstrate his ability to secure funding and lead research teams across various technical domains. Professor Yordanov has mentored six PhD students to completion, with several successfully defending dissertations on topics including intelligent energy systems, embedded real-time operating systems, and robotic systems. His academic leadership extends to serving as an academic mentor for over 600 student internships. His laboratory work centers on electrohydraulic control systems, robotic manipulation, and intelligent monitoring applications, with recent projects developing smart dispensers, beehive monitoring systems, and low-cost health monitoring devices for pregnant women, demonstrating practical applications of his theoretical research.

• Metrology
• Electromagnetic Field Measurement
• Power Quality
• +۴ مورد دیگر

Prof. Plamen Tsvetkov is a faculty member at New Bulgarian University (NBU) in the Department of Telecommunications since 2013. He previously held roles at Technical University of Sofia (1986–2019), including Head of the Department of Electrical Metrology (2004–2019). His academic career spans over 35 years in teaching and research. Education : PhD in Electrical Metrology from Technical University of Sofia (1998), specializing in robust structures for measurement systems. Research Interests : Metrology and calibration of measurement devices Power quality and electromagnetic field analysis Design of information-measurement systems Robust structures for measurement accuracy Applications in telecommunications and computer technology Recent Work Trends : His 15 most recent publications focus on power quality calibration methods, 4G/5G network protocols, and advanced signal processing techniques. Collaborations with international researchers emphasize standards like BDS EN 50160 and tools such as LabVIEW and MATLAB. Scientific Awards : Silver Medal, Technical University of Sofia Grants and Projects : Led 8 international projects and participated in over 30, including EU-funded initiatives on measurement standards and power quality. He also contributed to educational reforms in electrical engineering curricula. Publications and Leadership : Authored over 20 books and 130+ publications, with 15+ indexed in Scopus/Web of Science. Active in symposiums like International Symposium Metrology and Metrology Assurance as committee member.

• Digital Scenography
• Computer Graphics
• 3D Animation
• +۷ مورد دیگر

Petko Yakimov is an Assistant Professor at the Design Department of New Bulgarian University. With a PhD in Digital Scenography and Character in Cinema, his academic roles include teaching undergraduate courses in Human-Machine Systems and Image Analysis. He combines technical expertise with artistic sensibilities across multiple disciplines. PhD: Digital Scenography & Character in Cinema, New Bulgarian University (2016) MSc: Film & Television Direction, New Bulgarian University (2013) MFA: Scenography, National Academy of Arts (2001) BFA: Scenography, National Academy of Arts (1996) His research focuses on digital scenography , 3D animation , and virtual reality , with recent work exploring generative art techniques in Houdini and VR applications for museum visualization. Publications span topics from deepfake technology in artistic creation to 3D compositing workflows. Professional experience includes: Technical Specialist, NBU TV Studio (2019-2022) Lecturer in Multimedia & Virtual Reality at Academy for Musical, Dance and Visual Arts "Prof. Asen Sarafiev" (2018-2022) Leadership roles in computer graphics at Bulgarian National Television (2005-2011) CGI contributions to films like "Deep Shock" and "Dragon Fighter"

Sergey Vasilyevich Golubمشاهده پروفایل

استاد

• Agent programming
• Intelligent monitoring
• Medical informatics
• +۴ مورد دیگر

Sergey Vasilyevich Golub is a Professor at the Department of Software for Automated Systems at Cherkasy State Technological University. He holds a Doctor of Technical Sciences degree and has been part-time faculty since 2018. His career spans multiple roles, including dean at CHNU and head of departments in intelligent systems and software engineering. His research focuses on agent programming, intelligent monitoring, medical informatics, and machine learning. He has contributed to interdisciplinary projects linking software engineering with environmental monitoring and healthcare diagnostics. Recent publications emphasize multi-agent systems, social network analysis, and data-driven disease prediction. Key article trends include integrating satellite data for climate monitoring, authorship classification in social media, and agent-based modeling for pandemic forecasting. He collaborates with researchers in Ukraine and abroad, with works in Springer LNNS and CEUR-WS proceedings. Thanks and honorary diplomas from Cherkasy National University (2000, 2003, 2015) Honorary diplomas from Cherkasy Regional State Administration (2001, 2014) Honorary diploma from Ukraine's Ministry of Education and Science (2011) He has authored monographs on data analysis technologies and cross-platform decision support systems. His work bridges academic research and practical applications in intellectual monitoring across healthcare, ecology, and cybersecurity domains.

Kovalchuk Myroslav Lyubomyrovychمشاهده پروفایل

دانشیار

• Neural networks
• database organization
• creation of information systems
• +۱ مورد دیگر

Myroslav Lyubomyrovych Kovalchuk serves as an Associate Professor in the Department of Computer Science at Yuriy Fedkovych Chernivtsi National University. His academic foundation includes degrees in Electronics and Microelectronics, culminating in a Candidate of Physical and Mathematical Sciences qualification. His educational background comprises: Bachelor of Electronics, Yuriy Fedkovych Chernivtsi National University (2001) Engineer-physicist in Microelectronics and Semiconductor Devices, Yuriy Fedkovych Chernivtsi National University (2002) Candidate of Physical and Mathematical Sciences, Specialty 01.04.01 (2010) Kovalchuk's research centers on neural networks, database systems, information system development, and electronics engineering. His work bridges theoretical computer science with practical engineering applications, particularly in AI-driven solutions for real-world problems. He has developed specialized systems for image analysis, financial forecasting, and tourism infrastructure, demonstrating consistent innovation in computational methodologies. Over the past five years, his publication record reveals a strategic focus on neural network optimization, distributed database systems, and intelligent information architectures. His textbooks and research articles show increasing integration of cloud computing with traditional AI techniques, reflecting industry trends toward scalable, accessible computational solutions across finance, healthcare, and tourism sectors. Kovalchuk actively contributes to the Bukovina Information Technology Cluster (since 2019) and provides scientific consulting to KM TRADE LLC on security systems. He maintains professional currency through Sigma Software University's Teachers' Smart Up program and international training initiatives in Warsaw and Suceava, emphasizing modern pedagogical approaches for technical education.

• Machine Learning
• Ensemble Models
• Data Analytics
• +۵ مورد دیگر

Maria Vitalievna Talakh serves as an Assistant Professor in the Department of Computer Science at Yuriy Fedkovych Chernivtsi National University. Holding a Candidate of Biological Sciences degree, she bridges the gap between biological sciences and computer science with her unique interdisciplinary expertise. Education: Bohdan Khmelnytskyi National University of Cherkasy (2018): Systems Analysis, Qualification: Systems Analyst (Diploma with honors) Yuriy Fedkovych Chernivtsi National University (2004): Ecology and Environmental Protection, Qualification: Master of Ecology (Diploma with honors) Candidate of Biological Sciences (2009): Specialty 03.00.16 – ecology, dissertation on 'The role of the forest beech as an edificator species in the forest ecosystem' Research Interests: Dr. Talakh's research spans machine learning algorithms (particularly ensemble models), big data analytics, computer vision, and their applications in life sciences and ecological modeling. Her work demonstrates how computational methods can solve complex problems in environmental monitoring, medical diagnostics, and software engineering. She has developed intelligent monitoring systems for climate, air temperature, plant health, and software test automation, showing the versatility of her methodological approaches. Publication Trends: Her recent scholarly output reveals a strong focus on practical applications of machine learning across diverse domains. The majority of her publications from 2020-2024 explore convolutional neural networks, ensemble methods, and big data processing techniques applied to environmental monitoring, medical diagnostics, and software quality assurance. She frequently collaborates with researchers across disciplines, particularly with colleagues at her institution on projects involving satellite data analysis and ecological monitoring systems. Professional Activities: Member of the Bukovina Information Technology Cluster named after Joseph Schumpeter (Chernivtsi IT Cluster, Cluster Bit Association) since 2019 Scientific consultant for Limited Liability Company 'KM TRADE: Security Systems' (2019) Teaching: Dr. Talakh teaches courses related to data mining, intelligent data analysis, ensemble architectures, geoinformation systems, and big data technologies. She has authored numerous textbooks and teaching materials in these areas, demonstrating her commitment to both research and education in computational methods.

Tomka Yuriy Yaroslavovychمشاهده پروفایل

دانشیار

• Software architectures
• enterprise application development
• .NET platform
• +۳ مورد دیگر

Yuriy Yaroslavovych Tomka is an Associate Professor in the Department of Computer Science at Yuriy Fedkovych Chernivtsi National University. He holds a Candidate of Physical and Mathematical Sciences degree and has been serving as an Associate Professor since April 15, 2021. His academic work spans software engineering, neural networks, and biomedical image processing, with numerous publications in these fields. Dr. Tomka's educational background includes: Bachelor's degree in Laser and Optoelectronic Engineering from Yuriy Fedkovych Chernivtsi National University (2005), with honors Candidate of Physical and Mathematical Sciences degree (2009) in specialty 01.04.05 – Optics, Laser Physics Dr. Tomka's research interests focus on software architectures, enterprise application development on the .NET platform, pattern recognition, digital image processing, and neural networks. His work bridges theoretical computer science with practical applications in biomedical diagnostics, financial technology, and e-commerce systems. He has made significant contributions to the development of information systems, machine learning applications, and educational methodologies in computer science. Analysis of Dr. Tomka's recent publications reveals a strong focus on practical applications of software engineering principles, particularly in the .NET ecosystem. His work spans from fundamental software architecture to specialized applications in biomedical imaging and financial forecasting. There's a clear trend toward interdisciplinary research, combining computer science with fields like medicine and finance, demonstrating the versatility and applicability of his technical expertise. Dr. Tomka has received recognition for his mentorship, guiding student research that won second-degree diplomas in national competitions. His professional development includes numerous certifications in modern software technologies from institutions like Sigma Software University. As an active member of the Bukovina Information Technology Cluster named after Joseph Schumpeter since 2019, Dr. Tomka contributes to regional IT development initiatives. He also provides scientific consulting to the Limited Liability Company "Buknanotech" and has managed research projects including "Development of new methods and biomedical systems for polarization-holographic fractalmetry of crystallites of tissues and fluids of human organs" (2019-2021).

Ushenko Yuriy Oleksandrovychمشاهده پروفایل

استاد

• Information systems design
• Data mining
• Pattern recognition
• +۷ مورد دیگر

Yuriy Ushenko is Professor and Head of the Department of Computer Science at Chernivtsi National University named after Yuriy Fedkovych. An Academician of the Academy of Engineering Sciences of Ukraine (2021), he holds a Doctor of Physical and Mathematical Sciences degree with specialization in optics and laser physics. His interdisciplinary work bridges computer science, biomedical engineering, and optical diagnostics. His educational background includes: Master of Telecommunications from Chernivtsi National University (2003, Diploma with honors) Doctor of Physical and Mathematical Sciences (2015) in specialty 01.04.05 – Optics, Laser Physics Professor title in Computer Science (2017) Professor Ushenko's research focuses on information systems design , data mining , pattern recognition , and digital image processing with specialization in laser polarimetry and interferometry . His work pioneers Mueller-matrix tomography and polarization-correlation microscopy for biomedical applications, developing computational methods to analyze biological tissues and fluids for diagnostic purposes. Key innovations include 3D digital polarization-holographic histology for myocardial damage assessment and intelligent systems for disease identification from medical images. His publication trends reveal a strong emphasis on applying machine learning to biomedical imaging and geospatial analysis, with recent work spanning transformer-based lyrics generation, polarization-singular tissue processing, and migration forecasting systems. The research demonstrates consistent translation of theoretical optics into practical diagnostic tools. Scientific recognition includes: Academician of the Academy of Engineering Sciences of Ukraine (2021) As Director of the Bukovinian Innovation Technologies Cluster (since 2019), he leads regional IT initiatives while serving as Associate Editor for the SCOPUS Q3 journal International Journal of Image, Graphics and Signal Processing . His mentorship has guided students to international awards including ICYS silver medals and EUCYS special prizes. Current projects involve developing automated intelligent systems for LLC 'KM Trade' and advancing Mueller-matrix diagnostic techniques through international collaborations with Springer and SPIE conferences. His laboratory work centers on creating computational frameworks for polarization-correlation microscopy, with active teams developing laser autofluorescence polarimetry techniques and digital image processing pipelines for biomedical diagnostics. The research group maintains strong ties with international partners in optical engineering and medical diagnostics.

• Computer Measurement and Control Systems
• Automation of Experimental Research
• Artificial Intelligence
• +۷ مورد دیگر

Balovsyak Serhiy Vasyliovych is an Associate Professor at the Department of Computer Systems and Networks, Faculty of Physics, Yuriy Fedkovych Chernivtsi National University. He holds a Doctor of Technical Sciences degree with expertise spanning computer measurement systems, digital image processing, and X-ray diagnostics. His academic journey began with a Candidate's thesis in solid-state physics (2003) and culminated in a Doctoral dissertation on multilevel methods for processing electron diffraction and X-ray signals (2019). His educational background includes graduation from Chernivtsi State University, Faculty of Physics, Department of Radio Engineering (1995). His professional career evolved from Engineer in Solid State Physics (1995-2003) to Assistant Professor (2004-2006), culminating in his current position as Associate Professor since 2006. Dr. Balovsyak's research interests encompass development of computer measurement and control systems, automation of experimental research, artificial intelligence, pattern recognition, digital image processing, artificial neural networks, and genetic algorithms. His work bridges physics and computer science, particularly in applying computational methods to analyze X-ray and electron diffraction data. His publication record demonstrates a clear progression from fundamental physics research toward increasingly sophisticated computational methods for image processing and analysis. Recent work focuses on Gaussian noise estimation and removal, adaptive image filtering, and computer vision applications, while maintaining connections to his foundational work in materials characterization through X-ray techniques. Certificate of Honor from the Chernivtsi Regional State Administration to the 140th anniversary of the Chernivtsi National University Dr. Balovsyak has developed numerous educational materials including lecture notes and laboratory manuals on Computer Systems of Artificial Intelligence, Digital Image Processing Methods, and other computer science topics. His work demonstrates strong integration between theoretical knowledge and practical implementation, with multiple software systems and patents developed for image processing and materials analysis applications.

• Data Compression and Protection
• Telemetry Systems
• Reconfigurable Information Processing Systems
• +۶ مورد دیگر

Світлана Львівна Воропаєва serves as an Assistant Professor at the Department of Computer Systems and Networks within the Faculty of Physics at Yuriy Fedkovych Chernivtsi National University. Holding a Candidate of Technical Sciences degree (2012) with her dissertation on 'Computerized system of UV sources monitoring', she teaches Engineering Graphics, Computer Graphics, and Technology of Designing Computer Systems while maintaining active research in applied computer engineering. Education: Chernivtsi National University named after Yuriy Fedkovych, Faculty of Physics, Department of Electronic Computing Machines (2000) Her research centers on data compression and protection in telemetry reconfigurable information systems, with significant contributions across computer vision (handwritten text recognition, video parameter optimization), image processing (scanned document enhancement), UV radiation monitoring (Tensor-31M radiometer-dosimeter), and semiconductor photodetector systems. She specializes in hardware-software integration for real-time control applications, particularly in UV source management and smart home technologies, while developing advanced signal processing algorithms for spectral coordination and parameter stabilization. Analysis of her 15 most recent publications (2005-2018) reveals consistent focus on applied solutions bridging computer science and physical instrumentation. Her work demonstrates strong interdisciplinary collaboration, particularly with Vorobets and Dobrovolskyi teams, evolving from semiconductor interface modeling (2005-2007) toward practical implementations in computer vision (2018) and smart systems. Key thematic progression shows increasing emphasis on neural networks, parallel computing, and IoT-integrated hardware solutions while maintaining core expertise in radiation physics and optoelectronics. Professional development is evidenced by 15+ certificates (2019-2023) in digital competencies including Adobe Photoshop, project planning, active learning methods, and international conference participation (Austria, Czech Republic, Romania). Her technical leadership spans hardware-software co-design for UV monitoring systems, photodetector optimization, and embedded control modules, with consistent publication output in Ukrainian and international engineering venues.

• Digital Image Processing
• Artificial Intelligence Systems
• Computer Vision
• +۳ مورد دیگر

Odayska Khrystyna Saveliivna is an Assistant Professor at the Department of Computer Systems and Networks, Chernivtsi National University named after Yu. Fedkovych. She holds a Candidate of Technical Sciences degree with a thesis on "Methods and means of improving the visual quality of images in computerized optoelectronic systems" (2020). Her academic work focuses on digital image processing and artificial intelligence systems. Education: Chernivtsi National University (2013) - Computer Systems and Networks. Her research spans digital image processing techniques, particularly Gaussian noise estimation and removal, with applications in medical imaging and optoelectronic systems. She has contributed to international journals and conferences, including studies on neural networks for X-ray image analysis and bilateral filtration methods for medical imaging. Recent publications include "Software and hardware for determining Gaussian noise level in images" (2022) and "Adaptive oriented filtration of digital images in the spatial domain" (2019). Her work combines theoretical advancements with practical tools like hardware-software complexes for noise estimation and removal.

Atanas Atanasovمشاهده پروفایل

دانشیار

• Agricultural Machinery
• Precision Agriculture
• Beekeeping
• +۳ مورد دیگر

Atanas Atanasov is an Associate Professor and Head of the Department of Agricultural Machinery at the University of Ruse, Bulgaria. His academic career spans agricultural engineering with a dual focus on precision farming technologies and apicultural systems. Contact details include email aatanasov@uni-ruse.bg and phone +359 82 888 442. His research integrates advanced engineering principles with agricultural applications, specializing in agricultural machinery optimization, precision agriculture through UAV and satellite remote sensing, and honeybee population dynamics modeling. Key areas include vibration analysis in harvesters, NDVI-based crop monitoring, soil-water conservation practices, and mathematical modeling of bee colony health. His work bridges theoretical optimization techniques with practical field applications in sustainable farming systems. Analysis of his 2023-2025 publications reveals a strong emphasis on integrating deep learning with remote sensing for crop disease detection (particularly wheat rust), precision management of agricultural machinery fleets, and sophisticated modeling of honeybee colony collapse factors. His research consistently targets resource efficiency improvements in sloped land agriculture and innovative solutions for Varroa mite control in apiculture.