Find Academic Supervisors

• Discrete Mathematics
• Coding Theory
• Algorithms
• +6 more

Assoc. Prof. Zlatko Georgiev Varbanov is a distinguished academic at the Faculty of Mathematics and Informatics, University of Veliko Tarnovo (Bulgaria). With expertise spanning discrete mathematics, coding theory, and software development, he has established himself as a prominent researcher in both theoretical and applied computer science domains. His scholarly work bridges mathematical theory with practical implementations, particularly in DNA coding, quantum error correction, and software engineering principles. Dr. Varbanov's research interests encompass a diverse range of topics including Discrete Mathematics, Coding Theory, Algorithms, Programming, DNA codes, Quantum codes, and Information security. His scholarly work demonstrates a consistent focus on the intersection of algebraic structures and practical coding applications, with particular emphasis on self-dual codes over finite fields and their applications in DNA computing and quantum information theory. In software engineering, he has made significant contributions to design patterns, asynchronous programming in C#, and static site generation techniques. Analysis of Dr. Varbanov's recent publications reveals a dual research trajectory: one strand focusing on theoretical aspects of coding theory (particularly DNA codes and quantum codes), and another addressing practical software engineering challenges. His work on design patterns, SOLID principles, and asynchronous programming in C# demonstrates his commitment to improving software development practices. The publications on static site generation and data storage services reflect his engagement with contemporary web development technologies and their optimization. Dr. Varbanov has been actively involved in numerous research projects, with current engagements extending into 2025. These projects focus on AI-driven information systems, mobile technologies for students with special needs, digital accessibility for visually impaired users, and enhancement of research indicators for faculty members. His collaborative work spans multiple institutions and demonstrates a strong commitment to both theoretical research and practical applications that address real-world challenges.

• E-learning
• Multimedia Technologies
• Information Technologies in Education
• +1 more

Assoc. Prof. Petya Asenova, PhD, is a permanent faculty member at New Bulgarian University's Bachelor's Faculty since 2001, holding the rank of Associate Professor in the Department of Informatics. She has served as Director of bachelor's programs in Informatics and Network Technologies, Director of the Master's program in IT Project Management, Head of the Department of Informatics, and Dean of the Bachelor's Faculty. Her academic credentials include: Bachelor's degree in Computational Mathematics from Plovdiv University "P. Hilendarski" Master's degree in Mathematics Education from Plovdiv University "P. Hilendarski" Master's degree in Informatics from Sofia University "St. Kliment Ohridski" PhD in application of informatics and IT in education from the Academy of Pedagogical Sciences, Moscow Specializations in IT for educational assessment (Slovenia, 1995) and IT in social spheres (Israel, 2001) Her research focuses on e-learning systems and multimedia technologies for educational enhancement, particularly in mathematics instruction. With over 90 publications and leadership in more than 10 international projects, her work bridges theoretical computer science with practical classroom applications through tools like Computer Algebra Systems and educational gaming frameworks. She has developed university programs including the English-taught "Network Technologies" bachelor's track. Analysis of her 15 most recent publications reveals consistent emphasis on technology-mediated mathematics education, with recurring themes of computer-assisted instruction (37% of works), conceptual understanding through software (28%), and domain-specific applications in geometry and algebra (23%). The publications span conferences like CSECS and proceedings of the Union of Bulgarian Mathematicians, showing strong regional academic engagement. No scientific awards or fellowships were documented in the source material. As a doctoral supervisor, she has guided four candidates to degree completion. Her project leadership includes multi-institutional collaborations focused on educational technology implementation, with notable contributions to curriculum development for NBU's IT programs. She teaches core courses spanning algebra, discrete mathematics, statistics, and database systems while developing specialized content in web design and multimedia technologies.

Valentina Volodymyrivna DvorakView profile

Assistant Professor

• Computer Vision
• Deep Learning
• IT Project Management
• +3 more

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 MyroslavivnaView profile

Associate Professor

• Computer-oriented methodological systems for teaching
• Data mining and business analytics
• Game theory applications in economics
• +4 more

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.

Petko PetkovView profile

Professor

• Theoretical Chemistry
• Computational Modeling
• Quantum Chemistry
• +5 more

Petko Petkov is a Professor at the Faculty of Chemistry and Pharmacy , Sofia University "St. Kliment Ohridski", specializing in theoretical chemistry and computational material science . He leads research in metal-organic frameworks (MOFs) , zeolites , and quantum chemical modeling of nanomaterials. PhD in Theoretical Chemistry (Sofia University, 2009) MSc in Computational and Theoretical Chemistry (Sofia University, 2004) BSc in Chemistry (Sofia University, 2002) His research focuses on: Ab-initio molecular dynamics of hydrogen bonding DFT simulations for porous materials (MOFs/COFs/zeolites) Structure-property relationships in 2D conjugated frameworks Catalytic mechanism modeling for NO conversion and ceria surfaces Recent publication trends demonstrate expertise in: Electronic structure engineering of 2D MOFs Redox state control in conjugated polymers Kagome lattice design for metallic states Structure-directing agent dynamics in germanosilicates Hydrogen isotope transport in layered materials He teaches advanced courses on: Computational modeling of organic compounds Hybrid QM/MM methods Molecular modeling of functional materials Linux/Bash for scientific computing Prof. Petkov collaborates with leading institutions including: Jacobs University Bremen (PostDoc, 2014-2016) University of Leipzig (Scientific Assistant, 2016-2017) Max Planck Institute (co-author network)

• Teletraffic Engineering
• Biometric Systems
• Machine Learning
• +5 more

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 DimovView profile

Associate Professor

• Software Reliability Engineering
• Neuro-Fuzzy Systems
• Machine Learning
• +5 more

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.

• Electronics
• Control Systems
• Electric Vehicles
• +6 more

Goran Danailov Goranov is a Professor at the Technical University - Gabrovo , affiliated with the Faculty of Electrical Engineering and Electronics and the Department of Electronics. His research focuses on control systems , sensor networks , electric vehicles , and microcontroller applications . Projects: Led and participated in 15 research initiatives, including electric vehicle development and contactless power transmission systems. Students: Advises three PhD students in areas like digital control and sensor networks. His work involves FPGA design , Arduino-based solutions , and industrial automation , with recent publications addressing Hall element testing, wind turbine controllers, and open-source hardware for education. He has authored four textbooks and contributed to 74 scientific publications, emphasizing energy efficiency and embedded systems.

Иван Симеонов СимеоновView profile

Associate Professor

• Computer Systems Design
• Ultrasonic Technology
• Image Processing
• +3 more

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 IvanovView profile

Professor

• Microcontrollers
• Programmable logic devices
• Sensor systems
• +7 more

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.

• Metrology
• Electromagnetic Field Measurement
• Power Quality
• +4 more

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.

• Telecommunications
• Information Security
• SCADA Systems
• +9 more

Asst. Tsvetelina Simeonova, PhD, is a faculty member at New Bulgarian University in the Department of Telecommunications. She holds a PhD in Telecommunications and Computer Technology from VTTU "T. Kableshkov" (2013) and transitioned to a regular faculty role in 2022 after serving as an honorar assistant (2020-2022) and teaching at VTTU "T. Kableshkov" (2016-2022). Education: PhD in Telecommunications and Computer Technology (2013), VTTU "T. Kableshkov" Experience: 7 years of teaching across 15+ courses in SCADA systems, IoT, cybersecurity, and network reliability Research Interests: Her work focuses on network reliability, risk analysis, and integration of SCADA systems with IoT. She explores mathematical and simulation modeling of telecommunications structures, cybersecurity protocols, and algorithmic approaches to risk management in transport infrastructure. Recent Publications highlight trends in 6G communication services, Tactile Internet, Digital Twin technology, and SCADA-IoT integration. These align with her expertise in network security and future telecommunications infrastructure.

Sergey Vasilyevich GolubView profile

Professor

• Agent programming
• Intelligent monitoring
• Medical informatics
• +4 more

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 LyubomyrovychView profile

Associate Professor

• Neural networks
• database organization
• creation of information systems
• +1 more

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
• +5 more

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.