جست‌وجوی استاد و پژوهشگر

Valentina Volodymyrivna Dvorakمشاهده پروفایل

استادیار

• Computer Vision
• Deep Learning
• IT Project Management
• +۳ مورد دیگر

Valentina Volodymyrivna Dvorak serves as an Assistant Professor in the Department of Computer Science at Chernivtsi National University. Her professional activities span across computer vision, deep learning, IT project management, and business analysis, with significant contributions to both academic research and practical applications in these fields. Dr. Dvorak holds a Candidate of Technical Sciences degree with specialization in Pressure Processing Processes and Machines. Her educational background includes a Master's in Metallurgical Equipment (2004) and a degree in Organizational Management (2010) from Donbass State Machine-Building Academy. This unique combination of metallurgical engineering and computer science expertise informs her interdisciplinary research approach. Her research interests prominently feature Computer Vision and Deep Learning applications across diverse domains including medical diagnostics, satellite imagery analysis, and industrial process optimization. Dr. Dvorak has made significant contributions to convolutional neural network implementations, automated recognition systems, and polarization-correlation microscopy techniques for biomedical applications. Her work bridges theoretical computer science with practical implementations in healthcare, manufacturing, and environmental monitoring. Analyzing her publication record reveals a strong focus on practical applications of deep learning, with particular emphasis on computer vision systems for medical diagnostics, industrial quality control, and environmental monitoring. Her research demonstrates consistent progression from fundamental metallurgical process optimization to advanced AI applications. Certificate of acknowledgment as scientific supervisor for BLACK SEA SCIENCE 2022 Educational Grant from SoftServe for developing training course (2021) Dr. Dvorak actively contributes to IT education through multiple textbooks including 'Deep Learning for Computer Vision,' 'IT Project Management,' and 'Intelligent Data Analysis.' Her professional development includes numerous certifications from Sigma Software University and SoftServe, reflecting her commitment to staying current with industry practices. She serves as a member of the Bukovina Information Technology Cluster and provides scientific consulting for SKB 'Electronmash KM.'

Yatsko Oksana Myroslavivnaمشاهده پروفایل

دانشیار

• Computer-oriented methodological systems for teaching
• Data mining and business analytics
• Game theory applications in economics
• +۴ مورد دیگر

Yatsko Oksana Myroslavivna is an Associate Professor at the Department of Computer Science, Chernivtsi National University named after Yuriy Fedkovych. She holds a Candidate of Pedagogical Sciences degree (specialty 13.00.02 - theory and methods of teaching informatics) and has been certified as an Associate Professor since 2022. Her research focuses on computer-oriented methodological systems for teaching computer disciplines, with specializations in data mining for business applications, game theory implementation in economic decision-making, web technologies development, and algorithm design. She actively contributes to educational literature with multiple textbooks on Discrete Mathematics, Operations Research, Web Technologies, and Systems Modeling. Her professional engagements include membership in the Bukovina Information Technology Cluster, Chernivtsi Mathematical Society, and participation in international conferences like SPIE Optical Engineering and Correlation Optics. She has completed advanced certifications in machine learning, data visualization, and online education technologies from Prometheus, SoftServe, and other institutions. Her publications demonstrate expertise in strategic business analysis, cross-platform decision support systems, and educational software development. The 15 most recent works (2023-2024) cover data structures, game theory applications, web development tools, and polarization-based biomedical diagnostics. She serves as an expert for Ukraine's Ministry of Education and National Agency for Quality Assurance in Higher Education.

• Teletraffic Engineering
• Biometric Systems
• Machine Learning
• +۵ مورد دیگر

Dr. Georgi Ivanov Georgiev is an Associate Professor at the Department of Communication Equipment and Technologies , Technical University Gabrovo , with over 15 years of experience in teletraffic engineering, biometric systems, and artificial intelligence applications. He has led multiple research projects on network security, voice/facial recognition, and smart home systems. Current academic rank: Associate Professor Key collaborations: University of Ruse, IEEE, MDPI, AIP Publishing Research Interests : Biometric diagnostics with AI Machine learning for network traffic Neural networks (FFNN, GRNN, PNN) Smart home systems Teletraffic modeling Optical communication systems Recent Article Trends focus on hybrid AI methodologies (neural networks, decision trees, SVM) applied to: Noise analysis in communication systems Biometric authentication Internet traffic optimization Signal processing Smart environment monitoring Scientific Awards : Crystal Prize 2017 for Best Paper Multiple Best Paper awards at international conferences (2016, 2018) Student Advising : Reviewed thesis works on topics including Wind Farm Safety , Power Grid Modeling , and Lightning Protection Systems . Publications include 6 textbooks and 97 peer-reviewed works.

Aleksandar Dimov Dimovمشاهده پروفایل

دانشیار

• Software Reliability Engineering
• Neuro-Fuzzy Systems
• Machine Learning
• +۵ مورد دیگر

Aleksandar Dimov Dimov is an Associate Professor at the Department of Software Technologies, Faculty of Mathematics and Informatics (FMI), University of Sofia. He specializes in software reliability engineering, neuro-fuzzy systems, and cloud computing architectures. His research focuses on optimizing software systems through adaptive methodologies and addressing challenges in distributed computing environments. His work spans over two decades, with contributions to neuro-fuzzy optimization for manufacturing, machine learning applications in healthcare, and architectural patterns for scalable systems. Key areas include improving software reliability models, cloud storage performance, and privacy-preserving software design. He has published extensively on topics like microservices, service-oriented architectures, and educational technology. Dr. Dimov's publications reflect a strong emphasis on practical solutions for real-world challenges in software engineering and data systems. His research bridges theoretical models with applied implementations, particularly in domains requiring high precision and adaptability.

Nevyana Krastevaمشاهده پروفایل

استاد

• Marketing
• International Business
• Tourism Economics
• +۴ مورد دیگر

Nevyana Krasteva is a Professor of Marketing and International Business at Sofia University St. Kliment Ohridski and the International Business School, Botevgrad. She is a member of the American Marketing Association and European Management Council, with research spanning diverse marketing contexts including political environments, conflict zones, and cultural practices. Research Interests : Digital marketing, artificial intelligence applications, consumer behavior, augmented reality, tourism economics, and sustainable agricultural marketing. Publications : Focus on interdisciplinary topics like marketing philosophy, gamified education, and global consumer trends. Specializations : Has specialized in marketing practices across Russia, Austria, Greece, Denmark, Japan, Israel, and Hungary. Professional Memberships : American Marketing Association European Management Council

• Machine Learning
• Data Science
• Public Sector Digitalization
• +۳ مورد دیگر

Assoc. Prof. Boryana Pelova is an Associate Professor at the Department of Statistics and Econometrics, Faculty of Economics and Business Administration (FEBA), Sofia University. She holds a PhD and has over 15 years of expertise in data analysis, large dataset processing, and machine learning applications. Her work addresses societal challenges such as air quality improvement, mental health prevention, and digitalization of public sectors and SMEs. She currently leads research projects including 'Digitalization of SMEs' (2023–present), 'SHARE-ERIC Bulgaria' (2018–present), and a National Science Fund project (2023–present). Prof. Pelova serves as the Academic Director of the MSc Program 'AI for Business and Finance' and pioneered an industry-funded PhD program. She previously led the Career Center at FEBA (2016–2023), organizing career development initiatives for students. As former Vice-Dean of FEBA (2019–2023), she fostered academic-business collaboration to enhance tech-driven education. She also coordinates initiatives linking vocational schools with universities, such as the affiliation of the Burgas Vocational School of Computer Programming and Innovation with Sofia University. Her research focuses on applying data science to real-world problems, including financial stability and environmental sustainability. While no specific scientific awards are listed, her contributions to academic-industry synergy and educational innovation highlight her leadership in advancing tech-driven education and societal impact. Prof. Pelova collaborates with institutions such as the ESG Lab and Center for Education Services at FEBA, driving interdisciplinary projects like the Twin4Eco and ConsuWAIS initiatives. Her work emphasizes bridging academic research with practical solutions for businesses and public sectors.

Kaloyan Ganevمشاهده پروفایل

دانشیار

• Macroeconomic Modelling
• Econometrics
• Forecasting
• +۶ مورد دیگر

Assoc. Prof. Kaloyan Ganev holds a PhD in Statistics and Demography from the University of Sofia. He is affiliated with the Department of Statistics and Econometrics at the Faculty of Economics and Business Administration. His teaching portfolio includes courses such as Macroeconomic Modelling, Applied Econometrics, Time Series Analysis, and Public Finance. His research focuses on macroeconomic forecasting, applied econometrics, and historical economic analysis in transition economies. Prof. Ganev has over 20 years of practical experience in public and private sectors, including roles at the Agency for Economic Analysis and Forecasting (Ministry of Finance), Raiffeisenbank EAD, and Sigma Hat consultancy. He has also served as an international consultant for Montenegro and Belarus governments. His work bridges academic research with real-world policy implementation. His recent publications examine topics such as consumer price dynamics in Bulgaria, healthcare workforce shortages in post-communist contexts, and neurocomputational forecasting methods. He has contributed to understanding economic planning mechanisms in communist Bulgaria and the EU integration process's effects on economic indicators. Though no formal awards are listed here, his extensive consulting and applied research demonstrate impactful contributions to both academia and policy-making. His advising and grants focus on SME competitiveness, EU-funded policy assessments, and human capital analysis. He is actively involved in the Faculty's research initiatives and maintains a presence on ResearchGate for scholarly collaboration.

• Electromagnetism
• Antenna Engineering
• Semiconductor Technology
• +۲ مورد دیگر

Zlatan Dimirov is a researcher (R1) at the Faculty of Economics and Business Administration, Sofia University "St. Kliment Ohridski" since September 2024. He holds advanced degrees in engineering disciplines and has contributed to research in electromagnetism, semiconductor technology, and AI. Education: MSc in Electromagnetism, Nuclear Fusion, and Space Engineering from KTH Royal Institute of Technology BSc in Electrical Engineering and Information Technology from TU Wien and Aalto University Research Focus: Electromagnetism and Antenna Engineering Semiconductor Technology Artificial Intelligence and Machine Learning

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.

Yavor Ivanov Dankovمشاهده پروفایل

استادیار

• Educational Video Games
• Software Technologies
• Data Visualization
• +۵ مورد دیگر

Yavor Ivanov Dankov is an Assistant Professor in the Department of Software Technologies at the Faculty of Mathematics and Informatics, Sofia University 'St. Kliment Ohridski'. His academic career focuses on the intersection of educational technology, software engineering, and cultural heritage preservation. Dr. Dankov holds a PhD and has established himself as a specialist in educational video games, particularly those designed for cultural heritage education and climate resilience. His research interests center around user-centered design of educational video games, data visualization for learning analytics, and the development of instruments supporting game designers in creating effective educational experiences. Dr. Dankov's work bridges the gap between theoretical educational frameworks and practical software implementations, with strong emphasis on adaptive learning systems and personalized educational experiences. His research demonstrates how educational video games can be effectively leveraged for cultural heritage preservation and climate resilience education, particularly through the innovative DIZU-EVG (Data visualIZation instrUment for Educational Video Games) platform he has developed. Analysis of Dr. Dankov's recent publications reveals a consistent focus on the design, development, and evaluation of educational video games, with particular attention to cultural heritage applications. His work shows a progression from theoretical frameworks to practical implementations, with increasing sophistication in data visualization and learning analytics components. The research demonstrates strong interdisciplinary connections between computer science, education, and cultural heritage studies, with growing emphasis on practical tools that support both educators and game designers. Dr. Dankov has been actively involved in numerous research projects including the DIZU-EVG tool development (2024), MOTIVATE project on intelligent tools for adaptive educational games (2024), and various European Commission-funded initiatives such as UNITE and E-CREHA. His grant portfolio demonstrates significant expertise in securing competitive research funding at national and international levels. His work is organized around several key research groups focusing on educational video game design, data visualization for learning analytics, and cultural heritage applications. These teams collaborate across disciplines to develop innovative approaches to educational technology that combine software engineering excellence with pedagogical effectiveness.

• Foreign Language Education
• Computer-Assisted Language Learning
• Translation Studies
• +۳ مورد دیگر

Milen Chipchanov is an Assistant Professor at New Bulgarian University (NBU) in the Department of Foreign Languages and Cultures. He has over 35 years of teaching experience in French language education, focusing on courses such as written and oral translation, phonetics, and the integration of multimedia and new technologies in foreign language instruction.

• 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.

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.