Máté Szabó is an Assistant Professor at the University of Debrecen , affiliated with the Faculty of Informatics and the Department of Information Technology . His email contact is szabo.mate@inf.unideb.hu . He works in areas such as Machine Learning , Smart Cities , and Mobile Computing . His research spans topics like microservice architecture for ensemble models, Markov modeling of traffic flows, and distributed machine learning on mobile platforms. He has explored neural models for conversational AI and gamification in programming education through Minecraft-based challenges. His work also addresses edge computing and data parallelism in mobile environments. His publications (2016–2024) reflect trends in machine learning deployment on Android platforms smart city traffic analytics gamified educational tools cognitive modeling of numerical understanding microservice-based model integration .
Károli Gáspár University of the Reformed ChurchHungary
Dr. habil. Dringó-Horváth Ida is an Associate Professor at the Faculty of Humanities and Social Sciences of Károli Gáspár University of the Reformed Church in Hungary (KRE). She serves as Head of the ICT Research Center under the Rector's Office and as Head of the Educational Informatics Continuing Education Center at KRE BTK. Her leadership extends to multiple research projects focused on educational technology in higher education, particularly examining digital competencies, teacher development, and the integration of information and communication technologies in academic settings. Dr. Dringó-Horváth earned her PhD in German Studies/Linguistics from Eötvös Loránd University in 2004, with a dissertation titled "Analysis and Evaluation of the Modern Teaching and Learning Medium 'Elektronisches PC-Wörterbuch'." She completed her habilitation in Educational Science at the same institution in 2019. Her academic background includes an MA in German from Eötvös Loránd University (1998) and additional qualifications in educational informatics and social work. Her research focuses on the intersection of educational technology and higher education pedagogy, with particular emphasis on digital competence development for teachers, dictionary skills in language learning, and the digital transformation of educational practices. Dr. Dringó-Horváth leads the "Educational Informatics in Higher Education" research project, which examines effective learning/teaching opportunities in electronic learning environments and maps ICT indicators of higher education lecturers. Her work explores how reflection processes contribute to long-term teacher competency development in the digital age. Analysis of her recent publications reveals a strong focus on artificial intelligence in higher education, technostress reduction, and digital competence measurement. Her research shows how digital transformation impacts both teaching practices and student learning experiences. She has made significant contributions to understanding how educators develop digital competencies and integrate technology into their teaching practices across different disciplines. Károli Kiválóság Díj (2022) for Q1 publication Károli Kiválóság Díj (2023) for Q1 publication Károli Kiválóság Díj (2023) for Q2 publication A. S. Hornby Trust Grant for dictionary research presentation at EURALEX Conference Dr. Dringó-Horváth actively mentors doctoral students including Sebestyén Lilla Anna, Veres Violetta, and Gulmira Kusajynkyzy. She serves as institutional coordinator for multiple significant research projects including "PROFFORMANCE+" (2022-2025), "Ensuring Quality Digital Higher Education in Hungary" (2022-2023), and "Support of Digital Transformation of Hungarian Higher Education" (2021-2022). Her grant portfolio demonstrates strong institutional support for her work in educational technology and faculty development. As leader of the ICT Research and Training Centre (Educational Technology Research and Training Centre), Dr. Dringó-Horváth oversees a dynamic team conducting research on information and communication technologies in higher education. The center collaborates with international and domestic institutions to develop best practices for digital learning environments. Her team's work has significantly influenced Hungarian higher education policy regarding digital transformation and teacher development.
Dr. Gergely Kocsis serves as an Associate Professor at the University of Debrecen's Faculty of Informatics, Department of Informatics Systems and Networks. His office is located in the Faculty of Informatics building at 4028 Debrecen, Kassai út 26, ground floor, IF13 (Lecturers' room), with contact email kocsis.gergely@inf.unideb.hu and central telephone +36 52 512 900 75013. Dr. Kocsis's research program focuses on: Information spreading phenomena Agent-based and individual-based simulations Cellular automata applications Network structure and dynamics His scholarly output reveals a sophisticated research trajectory evolving from foundational work on cellular automata modeling of social dynamics (2007-2014) to contemporary investigations of transportation networks, VANETs, and AI applications. The 2023-2025 publications demonstrate particular expertise in network extraction methodologies, containerized computing environments, and the application of generative AI to productivity challenges. His work consistently applies computational modeling approaches to understand complex spreading phenomena across diverse network structures. Dr. Kocsis maintains comprehensive scientific profiles across major academic platforms including Google Scholar, ResearchGate, ORCID, Scopus, and Web of Science, demonstrating active participation in the international research community. His departmental colleagues work in complementary areas such as complex networks, embedded systems, and neural networks, suggesting rich collaborative opportunities within the Faculty of Informatics.
András Tibor Kertész is a Hungarian architect and academic born in 1955. He holds the rank of Professor at the Faculty of Engineering and Informatics, University of Pécs, since 2015. His career spans decades as the owner and chief designer of multiple architectural firms, including Kertész Architect Studio Ltd. (since 1996) and Avant-Garde Architectural Studio Ltd. (since 2009). He combines academic leadership with extensive practical experience in architectural design and urban projects. Education : Degree in Architecture (BME, 1979); Advanced French Language Exam (ELTE, 1985) Academic Credentials : DLA (Doctor of Liberal Arts) in Architecture (BME, 2005); Habilitation (PTE, 2014) His research interests focus on architectural innovation, urban development, and structural engineering, reflecting his involvement in landmark projects like the Pentele Highway Bridge and Balatonfüred Yacht Club. He has received numerous accolades, including the Miklós Ybl Award (1987) and Pro Architectura Award (2018), underscoring his contributions to architectural theory and practice. Professional Leadership : Active in urban planning councils (Budapest VII. District, Central Planning Council), former Ybl Award Committee member, and held leadership roles in MÉSZ (Hungarian Chamber of Architecture).
Budapest University of Technology and EconomicsHungary
Dr. Gergely Mezei is an Associate Professor and Deputy Head of the Department of Automation and Applied Informatics at the Budapest University of Technology and Economics (BME) , Hungary. He is affiliated with the Applied Computer Science Group within the department and is actively involved in research and education in model-driven engineering and formal methods. His research interests lie at the intersection of multi-level modeling , formal verification , and model transformation systems . He has contributed extensively to the development of modeling languages and tools, particularly in the context of DMLA (Deep Multi-Level Architecture) and Melanee , focusing on enabling rigorous, scalable, and verifiable modeling practices. Dr. Mezei's work emphasizes performance optimization in model transformations, visual modeling frameworks , and domain-specific languages . His research spans both theoretical foundations and practical tool implementations, with a strong focus on bridging the gap between formal semantics and usable modeling environments. His recent publications reflect a consistent focus on advancing the state-of-the-art in multi-level modeling and formal verification , with contributions to international workshops such as MULTI and MPM . These works explore challenges in model validation, transformation correctness, and the usability of modeling tools in complex systems engineering. Contact: Email: gmezei@aut.bme.hu Office: Q.B228, Budapest University of Technology and Economics, 1117 Budapest, Magyar tudósok krt. 2., Hungary Phone: +36 (1) 463-3491
Dr. Valéria Póser serves as Vice Dean of Education at the John Neumann Faculty of Informatics, Óbuda University, while also holding positions as Senate senator and Education Committee voting member. She earned her PhD in 2011 and maintains active research and administrative roles within the university. Her language proficiency includes English at Middle level and Russian at Basis level, supporting her international academic engagement. Dr. Póser's research focuses on software engineering with emphasis on artificial intelligence applications, information security, and educational technology. She has received multiple Dean's commendations in 2009, 2013, and 2016, recognizing her contributions to academic excellence. Her publication record remains active with recent works reflecting trends in intelligent systems, software development methodologies, and educational applications of technology. Dean's commendation 2009 Dean's commendation 2013 Dean's commendation 2016 As Vice Dean of Education, Dr. Póser oversees curriculum development, teaching quality, and educational innovation across the Faculty of Informatics. Her leadership connects academic research with practical implementation in technology education.
Dr. Zoltán Siménfalvi serves as Dean of the Faculty of Mechanical Engineering and Informatics at the University of Miskolc, Hungary, holding the academic rank of Professor. His leadership encompasses oversight of academic programs, research initiatives, and administrative functions within the faculty, positioning him at the forefront of mechanical engineering education and innovation in Central Europe. His research spans explosion protection, biogas technology, combustion engineering, and sustainable energy systems. Key focus areas include computational fluid dynamics (CFD) simulations for hazardous area classification, flash point determination of flammable mixtures, hydrogen/methane dispersion modeling, and optimization of anaerobic digestion processes. His work bridges theoretical analysis with industrial applications in energy safety and renewable resource utilization. Analysis of his 15 most recent publications (2022-2024) reveals dominant themes in explosion hazard analysis (60% of works), particularly 2D/3D hazardous area modeling, gas detector performance in ammonia environments, and FLACS-CFD simulations for hydrogen-methane mixtures. Biogas technology constitutes 25% of output, emphasizing mixing efficiency in anaerobic digesters and process optimization. Remaining research addresses sustainable engineering through carbon capture strategies for V4 countries, coal gasification efficiency, and propane leakage dynamics. No scientific awards were documented in the available materials. Information regarding student advising, research grants, or laboratory supervision was not provided in source materials. His administrative role as Dean suggests strategic oversight of research funding and academic programs, though specific grant details remain unreported. No dedicated research laboratories or specialized teams were explicitly referenced, though his publications indicate collaboration with computational modeling groups and industrial safety partners for experimental validation of CFD simulations.
Budapest University of Technology and EconomicsHungary
Krisztián Pomázi is a Lecturer at the Budapest University of Technology and Economics , affiliated with the Faculty of Electrical Engineering and Informatics and the Department of Automation and Applied Informatics . His work bridges educational technology and cognitive science , utilizing machine learning and bioinformatics to enhance learning experiences. Department: Automation and Applied Informatics Email: Pomazi.Krisztian@aut.bme.hu Research interests include: Adaptive learning systems integrating biofeedback Machine learning applications in cognitive workload assessment Psychological profiling using computational models Usability evaluation via biomedical signal processing Intelligent exercise generation for cognitive assessment Educational game mechanics with physiological feedback Recent publication trends show a focus on blending machine learning with human-computer interaction to create personalized educational tools. His work incorporates cognitive science principles to dynamically adjust learning environments using biofeedback data, while also exploring psychometric and usability dimensions in digital education. Contact: Pomazi.Krisztian@aut.bme.hu
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.
Eszter Rita Katona is an Assistant Professor at Eötvös Loránd University's Faculty of Social Sciences, Department of Social Research Methodology. She serves as a lecturer at multiple research centers including the Research Center for Computational Social Science (RC2S2), Survey Methods Room Budapest, and Széchenyi István College for Advanced Studies. Education: PhD in Interdisciplinary Social Research (Doctoral School of Sociology, 2018-2023) Computer Science specialization (Faculty of Informatics, 2016-2017) Survey Statistics MSc (Faculty of Social Sciences, 2015-2018) Social Sciences BA (Faculty of Social Sciences, 2011-2015) German Studies BA (Faculty of Humanities, 2012-2015) Angelusz Róbert College for Advanced Studies (2014-2018) Research Focus: As a computational social scientist, her work spans three major domains: NLP and data visualization applications in social research Discursive framing of depression in online communities Corruption risk assessment in public procurement Teaching Expertise: In her academic role, she teaches: BA courses: Data Collection Methods, Data Visualization, Introduction to Sociological Research, Quantitative Data Analysis MSc courses: Advanced Data Visualization, Python Programming, Communication and Data Visualization, Text Analytics Scientific Contributions: Her recent publications and conference presentations focus on: Machine learning for depression discourse analysis Digital lens approach to Holocaust testimonies Corruption risk modeling in public procurement Interdisciplinary NLP applications Computational social science methodology Contact: katona.eszter@tatk.elte.hu
Dr. Csaba Hegedűs is an active Associate Professor in the Department of Supply Chain Management at the University of Pannonia, Hungary, with office in Building "A", Room 121. He teaches core modules including Business Process Modeling and Re-engineering, Reliability and Risk Management, Quantitative Methods, and Production Quality Control, reflecting his operational research focus. Contact details are email: hegedus.csaba@gtk.uni-pannon.hu; phone: +36 88 624 – 106. Educational background: MSc in Engineering Management (2008) PhD (year unspecified) His research centers on Operations Management with interdisciplinary applications in industrial risk and uncertainty. Key areas include: Risk-based quality control systems Measurement uncertainty in conformity assessment Matrix-driven project planning frameworks Statistical process control under risk conditions Survival analysis of IT project management Decision support for industrial risk mitigation Publication trends (2013-2023) reveal sustained innovation in risk-modified control charts and matrix-based project libraries, bridging Operations Research, Statistics, and Industrial Engineering to address real-world uncertainty in quality decisions. Scientific awards: No documented awards in provided materials As Associate Professor, he likely supervises graduate research but no students are listed. His project experiences and GMT consultation role suggest applied industry collaborations, though specific grants or advising details remain unreported. Consultation hours require email pre-negotiation (Mondays 15:00-16:00). No dedicated laboratories or formal research teams are referenced in the available information.
Márton Karsai is an Associate Professor and Head of the Department of Network and Data Science at Central European University (CEU). He also serves as a Research Professor at the Rényi Institute of Mathematics (Hungary) and Editor-in-Chief of Advances in Complex Systems . His work focuses on computational social science, human dynamics, and data-driven modeling of socioeconomic systems. Karsai holds advanced degrees including a DSc from the Hungarian Academy of Sciences and an HDR (Habilitation) in Computer Science from École Normale Supérieure de Lyon. His research integrates temporal networks, human mobility, and social contagion phenomena, often using large-scale datasets from digital platforms and wearable sensors. Notable projects include studies on evacuation behavior during disasters, vaccination hesitancy, and urban socioeconomic stratification. Karsai leads interdisciplinary initiatives like the DyLNet project, which examines social interactions and language development in preschool environments through sensor technology. Recent publications highlight innovations in network clustering algorithms (PASCO), epidemic modeling with generalized contact matrices, and the application of machine learning to infer socioeconomic status from satellite imagery. His work bridges computational methods with real-world challenges in public health, urban planning, and humanitarian development.
Dr. Márta Seebauer is an Associate Professor at Alba Regia Faculty of Óbuda University. Her research spans interdisciplinary areas including artificial intelligence applications in energy systems, structural engineering reliability analysis, financial risk modeling, and sensor technology for food quality assessment. She maintains an active publication record with work showcased in IEEE symposiums and specialized journals. Email: seebauer.marta@uni-obuda.hu Consultation Hours: Thursdays 14:00-15:00 Her research interests emphasize practical applications of computational methods in civil, environmental, and smart city technologies. Recent work includes neural network-based energy monitoring systems and asbestos risk mitigation strategies during building demolition.
Ágnes Backhausz is a habilitated assistant professor at Eötvös Loránd University's Faculty of Science, Institute of Mathematics, Department of Probability Theory and Statistics, with a part-time research position at the Alfréd Rényi Institute of Mathematics. Her academic career spans theoretical probability and practical applications in network science. Dr. Backhausz's research focuses on probability theory with specializations in random graphs, matrices and their limits, spectral theory of random graphs, and factor of iid processes. Her work bridges pure mathematics with real-world applications, particularly in epidemiological modeling on complex networks. She has made significant contributions to understanding the eigenvectors of random regular graphs and the behavior of processes on infinite trees. Her recent publications demonstrate a growing emphasis on applying probabilistic methods to epidemic modeling on multilayer networks with overlapping communities. This research has important implications for public health policy and disease control strategies. The trend in her work shows increasing interdisciplinary collaboration, combining mathematical rigor with practical healthcare applications. Dr. Backhausz holds significant academic responsibilities including serving as Supervisor and training lead for the Beyond The Edge Marie Curie Doctoral Network (2024-2027) and as a researcher at the National Laboratory for Health Security, Hungary (2023-2026). She is an editor for Acta Mathematica Hungarica since March 2021 and has been organizing the Departmental seminar of the Department of Probability Theory and Statistics since 2010. She actively contributes to the mathematical community through program committee memberships for major conferences like Eurocomb and by organizing workshops on graph limits, groups, and stochastic processes. Her editorial work further demonstrates her standing in the mathematical research community. As an educator, Dr. Backhausz teaches mathematical statistics, probability theory, and related subjects across multiple programs at ELTE, including courses for mathematics students, earth science students, and informatics programs, showcasing the interdisciplinary nature of her expertise.
