Ildikó Horn is a Professor at the Eötvös Loránd University , where she serves as Director of the Institute of Historical Studies and works in the Department of Medieval and Early Modern History of Hungary . Her research focuses on Early Modern History , Renaissance Humanism , and the political elites of Transylvania , with particular emphasis on interdisciplinary networks and cultural exchange in divided Hungary (1541–1699). Her recent publications analyze the princely council under Gábor Bethlen , the construction of Transylvanian court culture , and the role of marriage alliances in elite power consolidation . She has contributed to comparative studies on European principalities and diplomatic information flow in the early modern period. Her work often intersects with digital humanities through the creation of databases on aristocratic networks . As an active participant in the academic community, she has published extensively in venues like the Hungarian Historical Review and Transylvanian Review , and her research has been cited in studies examining state formation , legal elites , and multi-ethnic societies in Central and Eastern Europe.
Budapest University of Technology and EconomicsHungary
Tamás Lovas serves as Associate Professor at the Department of Photogrammetry and Geoinformatics, Faculty of Civil Engineering, Budapest University of Technology and Economics. He teaches advanced courses in Building Information Modeling, Laser Scanning, Remote Sensing, and Intelligent Transportation Systems while supervising diploma theses in Surveying and Geoinformatics Engineering. Education: 1994: High school graduation, Városmajor High School, Budapest 1999: Certified Surveyor and Geoinformatics Engineer, Budapest University of Technology, Faculty of Civil Engineering 2005: PhD (Earth Sciences), Budapest University of Technology and Economics, Faculty of Civil Engineering Research Interests: Dr. Lovas specializes in laser scanning technologies and geospatial data processing with emphasis on airborne and terrestrial point cloud analysis. His work bridges civil engineering applications and computational methods, particularly in infrastructure monitoring and digital representation. Processing, classification, and modeling of airborne laser scanned data Accuracy testing of terrestrial laser scanning Processing and modeling of terrestrial laser scanned data Comparative study of spatial data acquisition technologies His 2022-2025 publications demonstrate accelerating integration of artificial intelligence in point cloud processing, with significant contributions to road surface extraction, urban land cover classification, and BIM automation. Current research trends show strong focus on digital twin development for autonomous vehicles and infrastructure management. Scientific Awards: Republic Scholarship (1998-1999) Karlsruhe Chancellor's Scholarship (1999) ERASMUS scholarship (2000) Korányi Fellowship (2001-2002) János Bolyai Research Scholarship (2008-2011) OHV 1st place (2008) Dean's commendation for ERASMUS committee work (2014) For Students Award - Teaching Department (2017) Advising and Grants: Dr. Lovas mentors students through diploma theses and TDK research projects on topics including object survey with amateur sensors and hull modeling. His research funding includes the prestigious János Bolyai Research Scholarship and international fellowships supporting collaborations with institutions like The Ohio State University. Labs and Teams: As founding member and supervisory board member of the Hungarian BIM Association, he drives industry-academia collaboration. His leadership roles include Deputy Dean of Education at the Faculty of Civil Engineering and responsibility for English language training programs, facilitating international academic exchange.
Dr. Gergely Vakulya is an Associate Professor and Research Fellow at Óbuda University. He specializes in interdisciplinary research spanning cybersecurity, agricultural technology, sensor networks, and image processing. His work integrates hardware design, algorithm development, and real-world applications. Dr. Vakulya’s recent focus includes developing rumen bolus sensors for dairy cattle health monitoring, gamification of cybersecurity training, and innovative methods in camera exposure time measurement. He is affiliated with Óbuda University’s Budai Road and Pirosalma Street campuses, with an office at building F room 316. His research frequently addresses challenges in data collection, sensor fusion, and embedded systems. Research Interests: Dr. Vakulya’s expertise includes cybersecurity frameworks (e.g., CTF challenges), agricultural IoT systems (e.g., rumen bolus sensors for livestock monitoring), and image processing techniques (e.g., genetic algorithms for shape approximation). His work on visible light communication (VLC) and wireless sensor networks highlights his contributions to communication protocols and energy-efficient systems. Recent trends in his publications emphasize cross-disciplinary approaches, such as applying AI methods to agricultural sensor data and optimizing sensor networks for real-time applications. Advising & Grants: No specific advising relationships or grants are listed in available materials. His research infrastructure is likely supported through institutional and collaborative projects. Labs/Teams: While not explicitly stated, his research likely involves collaborations within Óbuda University’s engineering and computer science departments. His work on rumen sensors and VLC systems suggests potential affiliations with robotics, biomedical engineering, or smart agriculture research groups.
Budapest University of Technology and EconomicsHungary
Professor Árpád Barsi is a faculty member at the Budapest University of Technology and Economics, Faculty of Civil Engineering, Department of Photogrammetry and Geoinformatics. He serves on the Habilitation Committee and Doctoral Council. His teaching subjects include Digital Earth, Photogrammetry, Geoinformatics, and Intelligent Transportation Systems. Research Focus: Digital photogrammetry, geospatial analysis, digital image processing, artificial intelligence, and vehicle navigation. Scientific Awards: #builder250 scholarship
Budapest University of Technology and EconomicsHungary
Charaf Hassan is a Professor and Head of Department at the Budapest University of Technology and Economics, specifically in the Department of Automation and Applied Informatics. His work spans interdisciplinary domains, focusing on distributed systems, network coding, and IoT technologies. His research interests include Distributed Systems and Domain-Specific Modeling Network Coding and Mobile Peer-to-Peer Systems Model-Driven Development for Multiplatform Applications Machine Learning in Fluid Dynamics and Pharmaceutical Analysis Recent publications highlight trends in applying convolutional neural networks to viscosity estimation, model-driven methodologies for IoT, and network coding in cloud storage. He teaches advanced courses in distributed systems and software architectures at the university level.
Ildikó Papp is an Associate Professor at the Faculty of Informatics, University of Debrecen , specializing in the Department of Data Science and Visualization . Her academic focus spans geometric modeling , 3D technologies , and experience-oriented teaching methods , bridging theoretical geometry with practical digital applications. Research Interests: Computer modeling of curves and surfaces Constructive and representational geometry 3D printing and visualization Cognitive infocommunication in education Publication Trends: Focus on QR code integration with 3D surfaces (2021-2022) Biomedical applications of FDM printing (2020) Educational impact of 3D technologies (2016-2018) Advancements in Bézier curve isoptics (2012-2013) Optimization techniques in geometric modeling (2012) Contact: Email: papp.ildiko@inf.unideb.hu
Róbert Tornai serves as an Associate Professor in the Department of Data Science and Visualization at the Faculty of Informatics, University of Debrecen, Hungary. His institutional affiliation encompasses active participation in the department's core mission of advancing data processing, visualization, and computational methodologies within Hungary's academic landscape. His primary research focuses on high-performance data transfer in supercomputing environments, parallel data processing using memory-safe Rust programming, and virtual collaboration system development. These interconnected domains emphasize optimizing data-intensive workflows while ensuring system security and user accessibility, reflecting contemporary challenges in distributed computing infrastructure. Analysis of his 15 most recent publications reveals dominant trends in high-speed connectionless networking protocols (2020-2025), where he investigates performance optimization, error detection, and encryption for file transfer systems. Significant secondary themes include biometric security applications (iris/voice recognition) and GPU-accelerated image processing techniques leveraging WebAssembly and Vulkan API, demonstrating technical versatility across networking, security, and visualization domains. His scholarly output consistently addresses practical implementation challenges in data transfer and secure systems, with recent work extending into educational technology applications of 3D printing. This trajectory indicates sustained engagement with evolving computational paradigms while maintaining focus on real-world system performance and security requirements.
Prof. Gyula Simon is a faculty member at Óbuda University's Alba Regia Faculty, where he holds the rank of Professor. His research focuses on sensor networks, localization systems, and signal processing. He has contributed extensively to advancements in technologies like TDOA-based positioning, VLC communication, and acoustic source tracking. With over two decades of academic work, his publications span applications ranging from agricultural sensors to fault-tolerant indoor positioning systems. Key research interests include developing robust localization algorithms for both outdoor and indoor environments, optimizing wireless sensor networks for energy efficiency and reliability, and integrating emerging technologies like visible light communication (VLC) for beaconing and tracking. His work bridges theoretical signal processing with practical implementations in fields like smart agriculture and security systems. Recent articles highlight innovation in hyperbolic localization methods, sparse sampling techniques for camera systems, and semi-automatic plant growth monitoring. Despite prolific publication output, no scientific awards are explicitly listed. Consultation hours are arranged via email at simon.gyula@amk.uni-obuda.hu, with his office located at Building F Room 316 in Székesfehérvár.
László Kovács serves as an Assistant Professor at the Faculty of Informatics, University of Debrecen, where he focuses on data science research and development. He is also recognized as an Nvidia Deep Learning Institute Certified Instructor and Ambassador, contributing to the advancement of AI education. His work is prominently featured through the Autonomous Vehicle Research Lab at the University of Debrecen. His primary research interests include Digital Image Processing , Fusion Systems , and High Performance Computing , with particular emphasis on medical applications. Kovács has developed data-driven solutions that address market, industrial, and social demands of artificial intelligence across various sectors including healthcare. His work demonstrates how the Faculty of Informatics at the University of Debrecen prioritizes data science in both educational and research contexts. Analysis of his publication record reveals a strong focus on medical image analysis, particularly in ophthalmology applications. His research consistently applies advanced computational techniques to solve diagnostic challenges in retinal imaging and melanoma detection. The publications show a progression from foundational algorithm development to practical medical applications, demonstrating his commitment to translating theoretical computer science into real-world healthcare solutions. Scientific Awards and Recognition: Ányos Jedlik PhD candidate scholarship of the National Excellence Program (2014-2015) János Csere Apáczai PhD scholarship of the National Excellence Program (2013-2014) Uiversitas scholarship from University of Debrecen (2012) Special prize at XXX-th National Scientific Students' Associations (2012) Prize of the Dean for Masters Students (2010) Kovács has supervised PhD research projects including OTKA NK101680 on melanoma detection and HURO/1001/283/2.3.1 on image-based recommendation systems. His teaching portfolio is extensive, covering High Level Programming Languages, High Performance Parallel Computing Tools, Parallel Image Processing, and Data Science. He has also established thesis topics in distributed programming, fusion systems, high-performance computing architectures, and medical diagnostic applications. His research group maintains an active GitHub presence through the Autonomous Vehicle Research Lab.
Dr. Carolin Hannusch is a Senior Lecturer at the Department of Computer Science, Faculty of Informatics, University of Debrecen, Hungary. She holds a B.Sc. (2009) and M.Sc. (2011) in Mathematics from the University of Debrecen, and completed her Ph.D. there in 2015. Her office is located in Room I129 of the Faculty of Informatics building. Her primary research focuses on algebraic coding theory and cryptography , with expertise in error-correcting codes, combinatorial designs, discrete mathematics, and applications in cybersecurity. She also publishes in mathematics education and digital text analysis. Her recent publications demonstrate strong interdisciplinary work across coding theory (e.g., binary self-dual codes, Goppa codes), cryptographic systems (e.g., hash functions, symmetric cryptosystems), and educational technology (e.g., digital text management, online trigonometry instruction). Awards include: Special Price at XXX. Students' Conference Hungary (2011) Universitas Prize for Young Researchers (2015) University of Debrecen's "Thesis of the Year" Prize (2018) She maintains collaborations with researchers across Europe and has presented work at international conferences including FedCSIS, CITDS, and Central European Conference on Cryptology.
Dr. Szilvia Szeghalmy is a Lecturer at the University of Debrecen, Faculty of Informatics, Department of Computer Science. She can be contacted at +36 52 512 900 75116 or via email at szeghalmy.szilvia@inf.unideb.hu, located in room I116, floor 1 of the Faculty of Informatics building. Her research focuses on: Digital Image Processing Imbalanced Learning Recent publications highlight trends in: Imbalanced data handling and noise filtering techniques (2024) Medical imaging applications (2024) Driver-assistance systems and traffic sign recognition (2018-2019) Human-computer interaction using sensors (2013-2014)
Budapest University of Technology and EconomicsHungary
János Török is an Associate Professor at the Department of Theoretical Physics, Budapest University of Technology and Economics, affiliated with the Morphodynamics group. His research spans granular materials, social network modeling, and morphodynamics of pebbles. Granular materials: Quasi-static shearing, shear band formation, particle shape effects, hopper flow Social science: Conflicts on Wikipedia, consensus modeling, social network dynamics Morphodynamics: Collective abrasion, fragmentation of pebbles His recent publications focus on computational modeling of granular physics and social dynamics, with applications in machine learning for malaria detection. Articles highlight interdisciplinary approaches to phase transitions, network analysis, and material deformation. Shear zones in granular materials Deep learning for social network parameters Malaria detection software He is involved in open-source projects (WWM, Mozi) and teaches courses in mathematical methods, mechanics, and scientific programming.
Dr. Bertalan Beszédes is a Senior Lecturer at Óbuda University's Alba Regia Faculty. His work focuses on control systems, renewable energy, and embedded electronics. He holds a consultation room at Building F, Room 321 in Székesfehérvár. His research emphasizes sustainable energy solutions, fault-tolerant systems, and automation applications in agriculture and manufacturing. Research interests include solar tracking systems, industrial welding control, and energy-efficient HVAC systems. He has contributed to projects involving smart security systems, vintage electronic device modernization, and educational robotics using LEGO Mindstorms. His publications span over two decades with a focus on embedded system reliability and renewable energy integration. Key innovations include off-grid power supply architectures and hybrid battery systems. His recent work (2023-2025) addresses challenges in smart agriculture, building automation, and legacy system upgrades. Beszédes maintains an active presence in both theoretical and applied electronics research.
Budapest University of Technology and EconomicsHungary
András Benedek is a University Professor and Head of the Department of Technical Pedagogy at the Budapest University of Technology and Economics (BME), Faculty of Economic and Social Sciences. Since 2005, he has also served as the Director of the Institute of Applied Pedagogy and Psychology at BME. With a career spanning over four decades in higher education (since 1982) and specifically at BME since 1986, he received his habilitation in 1996 and was appointed as a university professor in 1998. He became a doctor of the Hungarian Academy of Sciences in 2004. Professor Benedek's research interests focus on the evolving landscape of education in the digital age, with particular emphasis on Technical Pedagogy , Vocational Education , Mobile Learning , and Visual Learning . His work examines how technological advancements transform teaching methodologies and learning experiences, particularly in professional and vocational contexts. He has extensively researched the integration of ICT in education, the development of teacher competencies in digital environments, and the challenges and opportunities of lifelong learning systems. His publication record demonstrates a clear trend toward digital transformation in education, with increasing focus on visual learning paradigms, mobile learning applications, and innovative content development approaches. Recent work shows a strong emphasis on adapting educational systems to digital realities, particularly examining how the pandemic accelerated changes in educational delivery and necessitated new pedagogical approaches. His research consistently bridges theoretical pedagogical frameworks with practical applications in vocational and higher education settings. Throughout his distinguished career, Professor Benedek has held significant leadership positions both in academia and government. Between 1991 and 2006, he served in various high-level governmental roles including Deputy State Secretary of the Ministry of Labor, Ministry of Education, Ministry of Employment Policy and Labor, and Ministry of National Cultural Heritage. His expertise has significantly influenced Hungarian educational policy, particularly in vocational training and adult education. Professor Benedek directs the Institute of Applied Pedagogy and Psychology at BME, which serves as a hub for research and development in technical pedagogy, teacher training, and educational innovation. His department has been at the forefront of developing new approaches to vocational education and adapting traditional pedagogical methods to contemporary digital learning environments.
Zoltán Szegedy-Maszák serves as Professor and Head of the Doctoral School at the Hungarian University of Fine Arts, where he previously held roles including General Vice-Rector (2009–present) and Head of the Department of Fine Arts Theory (2009–present). His academic trajectory began with Assistant Professorship in the Department of Intermedia in 1997, advancing to Associate Professor in 2003 before achieving full Professor rank through his doctoral school leadership. Education highlights: DLA (Doctor of Liberal Arts, Fine Arts), Hungarian University of Fine Arts (2003) 'dr. habil' qualification (2007) Diploma in Intermedia Department (1994) Diploma in Painting Department (1992) Postgraduate studies, Hungarian University of Fine Arts (1992–1994) Szegedy-Maszák's research interrogates the philosophical and technical boundaries of digital creation, with sustained focus on experimental photography (notably camera obscura and photogram techniques), networked art systems, and interactive installations that challenge perception. His theoretical work explores media archaeology, digital preservation, and the interplay between artistic practice and technological innovation, often examining how obsolete media forms inform contemporary digital culture. This manifests in projects like 'Cryptogram' and 'Aura' that investigate data encryption, virtual realities, and illusion mechanisms. His artistic output reveals consistent engagement with digital imaging, web-based interactivity, and real-time data systems, evolving from early computer animations (1991–1999) toward complex networked installations. Key themes include the archaeology of computing, interface design as artistic medium, and the philosophical implications of digital reproduction—particularly evident in his 2000–2010 publications analyzing virtual environments and interactive frameworks. Notable recognition includes: Munkácsy Mihály Award (2010) Camera Obscura award at Hungarian Museum of Photography (2008) Ferenc Deák Post-Doctoral Scholarship (2003–2004) Derkovits Scholarship (1999–2002) European Media Artists Residency at Bauhaus Dessau (1995) As doctoral thesis supervisor since 2003, he has mentored emerging media artists while developing innovative curricula like 'Introduction to the (An)Archaeology of Computers'—an ongoing educational resource. His collaborative work with C3 Cultural and Communication Center (1996–2002) and projects like 'Exploration Network' demonstrate commitment to interdisciplinary knowledge exchange. Current initiatives focus on preserving digital art heritage through frameworks like the '404 Project,' addressing media obsolescence while exploring new frontiers in networked artistic practice.
