جست‌وجوی استاد و پژوهشگر

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.

Elena Dimitrova Monovaمشاهده پروفایل

استادیار

• Chaos Theory
• Control Theory
• Cyber-Physical Systems Security
• +۳ مورد دیگر

Elena Dimitrova Monova is a faculty member at the Technical University - Gabrovo, where she serves as an Assistant Professor in the Department of Automation, Information and Control Technology within the Faculty of Electrical Engineering and Electronics. Her academic career spans over two decades since completing her education at the same institution in 2002. Dr. Monova earned her higher education degree from the Technical University of Gabrovo in 2002, specializing in "Automation, Information and Control Engineering." Her academic journey led her to obtain a Doctorate (scientific and educational) in Technical Sciences. Her primary research interests focus on Chaos Theory and Control Theory , with significant expansion into related areas including cyber-physical systems security, data encryption using chaotic systems, and applications of artificial neural networks. Dr. Monova has established herself as a specialist in analyzing and controlling chaotic systems, with numerous publications exploring the Rucklidge model, Rikitake system, and other complex nonlinear dynamics. Analysis of Dr. Monova's publication record reveals a consistent research trajectory centered on chaotic systems and control theory, with recent expansion into practical applications involving artificial neural networks and cybersecurity. Her work demonstrates a progression from theoretical analysis of chaotic systems to practical implementations in areas such as secure communications, food quality assessment, and electromechanical systems. The interdisciplinary nature of her research connects electrical engineering, computer science, and applied mathematics. Electronic voting systems at Technical University - Gabrovo (2022) Security of cyber-physical systems in Industry 4.0 (2020) Systems for protecting classified information (2019, 2016) Digitalization of economy in big data environments (2018) International Erasmus+ projects including DISCOVER and MechMate Development of a smart medicine dispenser with privacy protection (2017) Her teaching responsibilities include courses on "Software Systems for Modeling and Simulation" and "Simulation and Modeling in Matlab" at the bachelor's level, reflecting her expertise in computational methods and system modeling.

• Control Systems
• Electro-Hydraulic Servo Systems
• Artificial Neural Networks
• +۴ مورد دیگر

Georgi Ivanov Mihalev is an Assistant Professor at the Technical University - Gabrovo, working within the Faculty of Electrical Engineering and Electronics, specifically in the Department of Automation, Information and Control Technology. Holding a Doctorate in Technical Sciences (scientific and educational), he has established himself as a significant contributor to control systems engineering and related fields. His academic career spans over a decade with continuous publication output since 2012. Dr. Mihalev's research interests focus on advanced control methodologies, particularly in electro-hydraulic servo systems, artificial neural networks applications, and image processing techniques. His work demonstrates a consistent pattern of applying theoretical control concepts to practical engineering problems across diverse domains including robotics, waste management systems, and image encryption. The breadth of his research shows particular strength in developing novel control algorithms that combine traditional approaches with machine learning techniques. Analysis of his publication record reveals a strong emphasis on practical implementation of control systems, with numerous papers addressing electro-hydraulic servo systems (appearing in approximately 40% of his recent work), followed by applications of artificial intelligence techniques to engineering problems. His 2025 Journal of Imaging paper demonstrates his expanding research scope into secure image transmission, showing increasing interdisciplinary work that combines control theory with cryptography. Dr. Mihalev has been actively involved in multiple international conferences in Bulgaria including AUTOMATICS AND INFORMATICS, UNITECH, and UTEOS symposiums, establishing himself as a regular contributor to the Bulgarian engineering research community. His collaborative work patterns show consistent partnerships with researchers including S. Yordanov, H. Stoycheva, and K. Ormandzhiev across multiple publications and research projects. His laboratory work appears to focus on practical implementation of control systems, with documented research on electro-hydraulic servo systems, robotic manipulators, vibratory bowl feeders, and intelligent waste collection systems. This suggests hands-on experimental research capabilities alongside theoretical contributions.

• Computer Architecture
• Parallel Computing
• Algorithm Design
• +۵ مورد دیگر

Associate Professor Yakovleva Inna Dmitrievna serves in the Department of Computer Systems and Networks at Chernivtsi National University's Faculty of Physics. With over two decades of academic experience, she has established herself as a prominent researcher in computer architecture and parallel computing. Her career progression from Assistant Professor (2003-2011) to her current Associate Professor position demonstrates her commitment to the institution and field. Her educational background includes a degree from Chernivtsi State University named after Yu. Fedkovych (Faculty of Physics, Department of Computer Science, 1993) followed by candidate studies at Lviv Polytechnic National University (2004-2007). She earned her Candidate of Technical Sciences degree in 2010 with a thesis on "Methods and tools for designing algorithmic operating devices with graphical representation of executed algorithms". Professor Yakovleva's research spans specialized computer systems, theoretical foundations of computer construction, data stream processing, algorithm development, parallelization techniques, and specialized processor design. Her work demonstrates a consistent focus on bridging theoretical computer science with practical hardware implementation, particularly through graphical representations of algorithms. She has made significant contributions to structural matrix representations of algorithm flow graphs and parallel computing architectures. Her publication record shows a strong trajectory in algorithm representation methods, evolving from foundational work on structural matrices to applications in smart home technology, voice control systems, and image processing. Recent publications indicate expanding interests in AI applications while maintaining core expertise in parallel computing and hardware design. Certificate of Appreciation from Ministry of Education (2023) 5 Years of Service Instructor Certificate (2021) Honorary Certificate from Regional Authorities (2019) Multiple EarthRover competition awards (2011-2018) Professional certifications in Linux, Cisco, and ChatGPT technologies Professor Yakovleva teaches System Software, VHDL Design Technology, Linux System Administration, and Cisco NDG Linux Essentials. Her professional development includes numerous certifications reflecting current industry trends. While the text doesn't detail specific mentoring activities, her extensive publication record with multiple co-authors suggests active collaboration with students and colleagues. Her work with research teams is evident through numerous joint publications, particularly with colleagues like Melnyk A.O. and Lisovenko I.D.

Evgenia Dimitrova Velikovaمشاهده پروفایل

دانشیار

• Coding Theory
• Algebra
• Information Theory
• +۳ مورد دیگر

Dr. Evgenia Dimitrova Velikova is an Associate Professor in the Algebra Department at the Faculty of Mathematics and Informatics, Sofia University "St. Kliment Ohridski". Her academic career spans several decades with significant contributions to both theoretical mathematics and educational research. Her research interests focus primarily on coding theory, particularly covering radius of linear codes, cyclic codes, and weight distributions. She has also made notable contributions to the field of educational assessment within mathematics education, analyzing student admissions processes and examination systems at her institution. Her work bridges theoretical mathematics with practical applications in both information theory and educational systems. Analysis of Dr. Velikova's publication history reveals a strong trajectory in coding theory research from the 1980s through the 2000s, with a notable shift toward educational research and interdisciplinary applications in digital humanities during the 2010s. Her later work demonstrates expertise in applying mathematical concepts to art image analysis and metadata extraction, showing versatility across multiple domains while maintaining her core mathematical foundation. Dr. Velikova has collaborated extensively with researchers including Ts. Baicheva, A. Bojilov, K. Ivanova, and P. Stanchev. Her work on covering radii of linear codes has been cited in numerous publications, including significant references in "Covering codes" by Cohen, Honkala, Litsyn, and Lobstein (1997), indicating substantial impact in her field. Her research has appeared in prestigious journals such as IEEE Transactions on Information Theory and SERDICA Journal of Computing. As an educator at Sofia University's Faculty of Mathematics and Informatics, Dr. Velikova has contributed significantly to curriculum development and educational assessment. Her office is located in room FMI-518, with office hours on Mondays from 13 to 15 at room 208 and Tuesdays from 13 to 14 at room 518, demonstrating her active engagement with students and academic community.

Plamen Maldzhanskiمشاهده پروفایل

استاد

• Photogrammetry
• Digital Photogrammetry
• Image Processing
• +۵ مورد دیگر

Prof. Dr. Eng. Plamen Maldzhanski is a Professor in the Department of Photogrammetry and Cartography at the Faculty of Geodesy, University of Architecture, Civil Engineering and Geodesy (UACEG) in Sofia, Bulgaria. He maintains office P228 and holds reception hours on Wednesday from 12-13. His academic career spans several decades, with significant contributions to photogrammetry, digital image processing, and geospatial technologies. Education Engineer in Geodesy, Photogrammetry and Cartography (1985), UACEG-Sofia Computer Engineering (1993), Technical University of Sofia Doctor of Photogrammetry and Remote Sensing Methods (1998), UACEG-Sofia Professor of Photogrammetry and Remote Sensing Methods (2012), UACEG-Sofia Research Interests Prof. Maldzhanski's research spans multiple areas within photogrammetry and geospatial technologies. His primary focus is on developing advanced methods for image processing and 3D modeling. He has made significant contributions to both theoretical frameworks and practical applications of photogrammetric technologies, particularly in architectural documentation and cultural heritage preservation. His expertise encompasses: Analytical and digital photogrammetry Close-range photogrammetry and laser scanning 3D modeling of surfaces and architectural structures Digital image processing and analysis Integration of photogrammetric data with GIS systems Development of specialized software for geodetic applications Publication Trends Prof. Maldzhanski's publication record demonstrates a clear evolution from traditional photogrammetric methods toward digital and computational approaches. His recent work (2017-2023) focuses heavily on photorealistic modeling, close-range photogrammetry applications for cultural heritage documentation, and integration of modern technologies like Google Maps API with geospatial data. His publications reveal a strong emphasis on practical applications in architectural documentation, precision measurement, and digital preservation of cultural sites. Awards and Professional Recognition Member of the Union of Geodesists and Land Surveyors Licensed professional for cadastral work (License No. 157) Full design capability license from KIIP Academic Leadership and Grants Prof. Maldzhanski has held significant administrative positions including Vice-Dean for Academic Affairs at the Geodesy Faculty and Vice-Rector for International Cooperation and Postgraduate Qualification. He has participated in multiple research projects funded by academic and government institutions, focusing on satellite imagery applications, architectural photogrammetry for cultural heritage documentation, and development of spatial data infrastructure. His grant activities include: "Използване на космически снимки за целите на регионалното и териториално планиране" (2007) "Възможности за създаване и обновяване на навигационни карти" (2008) "Използване на архитектурната фотограметрия при документиране паметници на културата" (2009) "Академичен център 'Дистанционни изследвания и мобилна инфраструктура на пространствени данни'" (2009) Software Development and Technical Contributions Prof. Maldzhanski has developed several significant software packages that bridge theoretical photogrammetry with practical applications: "PHOTO" software package for analytical photo processing and digital mapping "Geodesy" software for geodetic tasks, network adjustment, and terrain modeling "TEST_RGO" program for testing geodetic measurements according to Regulation 19 of the Cadastre Agency

Silvia Katsarska-Filipovaمشاهده پروفایل

دانشیار

• Photogrammetry
• Remote Sensing
• 3D Modeling
• +۵ مورد دیگر

Silvia Katsarska-Filipova is an Associate Professor at the Department of Photogrammetry and Cartography within the Faculty of Geodesy at the University of Architecture, Civil Engineering and Geodesy (UACEG) in Sofia, Bulgaria. She holds a Doctor of Science degree in Photogrammetry and Remote Sensing Methods (2014) and a Master of Science in Geodesy from the same institution (1995-2000). Currently, she teaches courses including Unmanned Aerial Photogrammetry and Transformation and Interpretation of Space Images, and conducts exercises in Digital Photogrammetry, Close-range Photogrammetry and Laser Scanning. Doctor of Science in Photogrammetry and Remote Sensing Methods (2014) Master of Science in Geodesy, University of Architecture, Civil Engineering and Geodesy (1995-2000) Dr. Katsarska-Filipova's research focuses on digital photogrammetry, image processing, 3D modeling of surfaces and volumetric bodies, methods for obtaining and analyzing geospatial information, unmanned aerial systems for image capture and processing, applications of remote sensing, and GIS. Her work bridges theoretical advancements with practical applications in cultural heritage documentation, environmental monitoring, and urban planning. She has developed expertise in using drone technology for precise geospatial measurements and analysis, particularly for volume computations in quarries and other applications. Her recent publications (2022-2024) demonstrate a strong focus on integrating photogrammetry with remote sensing for diverse applications including urban heat island analysis, forest fire monitoring, water body assessment, and photovoltaic park efficiency evaluation. She has increasingly incorporated digital twin technology and multi-sensor approaches in her research, showing a progression from traditional photogrammetric techniques to more integrated, technology-driven solutions that combine close-range photogrammetry, laser scanning, and satellite imagery. Her work frequently involves practical applications in environmental monitoring and cultural heritage preservation. Dr. Katsarska-Filipova has supervised numerous diploma students on topics ranging from photogrammetric documentation of architectural heritage to analysis of burned territories using satellite imagery. She has served as Quality Manager for her department since 2017 and has participated in multiple research projects including 'Information platform for research and monitoring of the environment' (2018-2019), 'Use of multispectral and thermal images in analysis and assessment of energy efficiency' (2021-2022), 'Creation of 3D models of architectural objects based on hybrid technology for laser scanning' (2022-2023), and 'Digital geodetic twins in UACEG' (2023-2024). She is a member of the Union of Geodesists and Land Surveyors in Bulgaria and has received positive assessment from the Commission for the Attestation of the Academic Staff at the Faculty of Geodesy of UACEG (375.9 points) dated January 7, 2020. Her research has been widely cited internationally, particularly her 2016 work on volume computation of stockpiles using UAV measurements, which has become a reference in the field of drone-based surveying applications.

Iglika Getovaمشاهده پروفایل

دانشیار

• Online Learning
• E-Learning
• Educational Technology
• +۴ مورد دیگر

Iglika Getova serves as an Associate Professor at the University of Library Studies and Information Technologies in Sofia, Bulgaria, within the Faculty of Information Science. With 21 publications and 43 citations recorded on ResearchGate, her academic profile demonstrates consistent scholarly productivity spanning from 2016 through upcoming 2025 research. Dr. Getova's research expertise encompasses multiple dimensions of educational technology: Online and hybrid learning methodologies Artificial intelligence applications in education Virtual and augmented reality implementations Knowledge assessment and evaluation systems Curriculum development for technical subjects Cybersecurity training frameworks Her publication trajectory reveals an evolving research focus from general e-learning topics toward increasingly specialized applications of emerging technologies. The most recent work (2023-2025) examines generative AI tools, VR for special education, and mixed reality in scientific visualization, while earlier publications (2018-2022) established foundational work in hybrid learning models and pandemic-era educational adaptations. Dr. Getova maintains an active collaborative network, primarily working with colleagues at her home institution including Iva Kostadinova (with whom she shares laboratory affiliation), Katia Rasheva-Yordanova, and Nikolay Ivanov Yanev. Her interdisciplinary approach connects education theory with practical technological implementations across various academic domains.

• Artificial Intelligence
• Machine Learning
• Telecommunications
• +۴ مورد دیگر

Ivelina Stefanova Balabanova is an Associate Professor at the Technical University of Gabrovo, Faculty of Electrical Engineering and Electronics, Department of Communication Equipment and Technologies. She holds a Doctor of Technical Sciences degree and leads research in AI-driven telecommunications and biometric systems. Research Focus: Her work integrates artificial intelligence, machine learning, and optimization techniques across domains including: Biometric security systems (voice/facial/fingerprint recognition) Network traffic analysis and prediction models Signal processing and noise identification in communication systems Telecommunication infrastructure optimization Publication Trends: Recent works (2022-2024) demonstrate strong emphasis on neural network applications for biometric authentication, network traffic forecasting, and signal processing optimization, with frequent use of FFNN, CFNN, and DWT methodologies in telecommunications contexts. Awards: Crystal Prize for Best Paper (2017) Crystal Prize for Best Paper (2015) Advising: Currently supervising three PhD students in telecommunications AI research: Teodora Valentinova Zhorova Kristina Maximova Sidorova Toni Ivanov Naydenov Projects: Leads teams of 12-19 researchers on institutional projects like 'Synthesis of intelligent object recognition systems' (2022) and participates in cross-disciplinary ICT initiatives including the national 'Digitalization of the economy in a Big Data environment' project.