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 .
László Lengyel is a Professor at the Budapest University of Technology and Economics (BME), affiliated with the Department of Automation and Applied Informatics . His work bridges theoretical and applied computer science, focusing on industrial automation, IoT systems, and model-driven engineering. Research interests include Model transformations and domain-specific languages IoT device management and multi-domain integration Software obfuscation and cybersecurity Graph algorithms and distributed computing (MapReduce) Real-time data analysis in manufacturing Automotive sensor networks His recent publications reflect expertise in model-driven IoT architectures , granule manufacturing automation , and MapReduce-based graph analysis , with a focus on industrial and automotive applications. He contributes to open-source frameworks like SensorHUB and explores gamification in driver behavior systems.
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.
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.
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.
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.
Balázs Lénárt is a researcher at the Department of Material Handling and Logistics Systems within the Faculty of Transportation Engineering at Budapest University of Technology and Economics (BME). He has maintained continuous academic activity since at least 2000, initially working at the Department of Transportation Operations (2000-2012) before transitioning to his current department in 2012. His research profile demonstrates significant contributions to logistics and transportation engineering with 21 publications and 63 total citations. Lénárt's research spans multiple dimensions of modern logistics systems, with particular emphasis on computational intelligence applications. His work explores the intersection of traditional logistics with emerging technologies, including ant colony algorithms for route optimization, cloud computing implementations for supply chain management, and even innovative concepts in space logistics for interplanetary supply chains. His publications reveal a consistent focus on improving efficiency in transportation networks through advanced algorithmic approaches and AI-driven solutions. Analysis of his publication trends shows an evolving research trajectory from foundational transportation operations (2008-2012) toward more sophisticated computational methods and emerging technology applications (2012-2019). His most impactful work appears in multimodal transportation planning and cloud-based logistics systems, with several publications receiving notable independent citations. The interdisciplinary nature of his research connects computer science, operations research, and traditional transportation engineering. Lénárt has collaborated extensively within the BME research ecosystem, particularly with colleagues Géza Katona, János Juhász, and Krisztián Bóna. His work has appeared in reputable journals including Periodica Polytechnica Civil Engineering and Transportation Research Proceedings, with several publications classified in Scopus Q2-Q3 journals. His research demonstrates practical applications for both terrestrial and conceptual space-based logistics systems.
Margit Makó is a Lecturer at Óbuda University, affiliated with the BUDAi Road Campus (8000 Székesfehérvár, Budai út 45). Her research focuses on electronics engineering, embedded systems, and circuit design, with a particular emphasis on Field-Programmable Analog Arrays (FPAA), control systems, and educational technology. She has published extensively on topics including analog circuit robustness, sensorless motor control, and hybrid feedback circuits. Her work often bridges theoretical concepts with practical applications, such as developing educational measurement laboratories and optimizing pneumatic cylinder control systems. Recent contributions include innovative FPAA-based solutions for circuit testers and hybrid systems. While her primary expertise lies in electronics, she has also explored interdisciplinary areas like mathematical modeling of germination kinetics and comparative pedagogy analysis between Hungary and France. Makó’s articles reflect a strong trend toward real-time systems, fault-tolerant design, and reconfigurable hardware. Her research highlights the integration of microcontrollers with FPAA for enhanced system performance. No scientific awards are explicitly mentioned in the provided materials. Consultation hours are held weekly on Mondays from 10:40 to 11:25 in Room 24 of Building K at the BUDAi Campus. She can be reached at mako.margit@amk.uni-obuda.hu for academic inquiries.
Dr. Imre Varga serves as an Associate Professor at the Department of Information Systems and Networks within the Faculty of Informatics, University of Debrecen. His academic profile centers on complex systems and networks, utilizing advanced computer simulations to model real-world phenomena across diverse domains including transportation infrastructure, epidemiological dynamics, and biological systems. His research spans complex network theory with emphases on transportation networks (GTFS/VANETs), epidemic spreading models (notably AI-driven COVID-19 prediction), molecular landscapes in metabolic diseases, and genealogical network analysis. Methodologically, he employs agent-based simulations, network extraction techniques, and spectral graph analysis to investigate structural properties and dynamic behaviors in interconnected systems. Current projects focus on real-time transit data processing and urban mobility optimization. Analysis of his 15 most recent publications reveals a strong trend toward applied network science: 60% address transportation/urban systems (GTFS extraction, VANET communications), 20% focus on epidemiological modeling (including dual publications on AI-based pandemic prediction), and 20% explore biomedical networks (molecular landscapes, comorbidity analysis). His work consistently bridges theoretical network properties with practical implementations in smart-city applications and public health. The Department of Information Systems and Networks, led by Dr. Zoltán Gál, provides a collaborative research environment where Dr. Varga contributes to initiatives in queuing theory, stochastic process modeling, sensor networks, and embedded systems. Key departmental research groups focus on Real-time Communication, Multimedia Systems, and Internet of Things applications, aligning with his work on vehicular networks and urban mobility systems.
Gyenes Károly is an Associate Professor at the Budapest University of Technology and Economics within the Department of Control for Transportation and Vehicle Systems. He also serves as Vice Dean and has a career spanning over five decades in transportation engineering, railway systems, and vehicle mechatronics. Languages: English, German Education: Electrical Engineering M.Sc. (1968), Ph.D. (2000), and multiple specialized diplomas Research Focus: Fail-safe railway interlocking systems, intelligent vehicle tracking (GPS/WiFi), microcontroller applications in traffic control, and secure data transmission protocols. His work bridges computer science with transportation engineering to enhance safety and automation. Key Publications Trends: Focus on railway automation, data transmission security, and microcontroller-based solutions. Articles span from 1975 to 2000, highlighting innovations in metro modernization, CRC error analysis, and remote control protocols. Scientific Awards: Minister of Education Award Educational Contributions: Taught courses in Computing, Computer Hardware, and Electronics at both undergraduate and postgraduate levels. Authored textbooks on programming and railway safety systems. Collaborations: Long-term involvement with Siemens, HungaroControl, and Robert Bosch in industrial projects. Key role in EU-funded research initiatives like the Tempus Project.
Anna Magi is a Lecturer at the Institute of Psychology and Department of Clinical Psychology and Addiction at Eötvös Loránd University. Her research focuses on addiction disorders, behavioral addictions (work, gaming, gambling), substance use epidemiology, and psychopathology. She actively participates in the Addiction Research Group and Criminal Psychology Research Group. Current roles: Lecturer in Clinical Psychology and Addiction Research areas: Reward deficiency, emotion regulation, genetic factors in addiction Key collaborations: Psychological and Genetic Factors of Addictive Behaviors (PGA) Study, National Survey on Addiction Problems in Hungary (NSAPH) Anna's recent publications analyze intersections between substance use and behavioral addictions, including work addiction, gaming disorder, and gambling. Her work employs psychometric tools, genetic polymorphism analysis, and population-wide surveys to explore risk factors, comorbidities, and preventive strategies. She contributes to methodological advancements in addiction research, demonstrated through studies like the development of the Reward Deficiency Syndrome Questionnaire (RDSQ-29) and validation of screening tools for cannabis and exercise dependence. Her research bridges psychological, biological, and sociocultural dimensions of addictive behaviors.
David Vincze is a researcher at the Department of Precision Mechanics, Chuo University, Japan. Previously affiliated with the University of Miskolc, Hungary, he has taught courses in Operating Systems, UNIX System Administration, and Modern Information Technologies. His research spans computational intelligence, fuzzy systems, reinforcement learning, and human-robot interaction. PhD in Computer Science Current Position: Researcher, Chuo University Previous Affiliation: University of Miskolc David Vincze's research focuses on Fuzzy Systems , particularly Fuzzy Rule Interpolation (FRI) , and its integration with Reinforcement Learning (e.g., FRIQ-learning). He applies these methods to Human-Robot Interaction (HRI) , drawing inspiration from ethology and animal behavior. His recent work explores applications in Parent-Child Interaction Therapy (PCIT) , using social robots to support child development and family communication. He also investigates Operating Systems Security , especially Linux kernel mechanisms. His publications show a consistent trend in developing and optimizing FRI-based learning methods for real-time, embedded, and robotic applications. He has worked on performance optimization, parallelization, and knowledge injection in FRIQ-learning, aiming to make fuzzy reinforcement learning more efficient and applicable in dynamic environments. Scientific Contributions: Developed FRIQ-learning: Fuzzy Rule Interpolation-based Q-learning Applied ethological models to robot behavior Designed fuzzy automata for HRI Optimized fuzzy inference for real-time systems Explored indoor localization for HRI experiments Vincze has advised students such as Alex Tóth and has been involved in student supercomputing teams (ASC 2014–2017). He has developed various Linux tools, including security extensions for Apache, video filters for MPlayer, and drivers for TV tuner cards. He maintains active research profiles on ResearchGate, Google Scholar, and Scopus. He leads projects in Mihoko Niitsuma's Lab at Chuo University, focusing on social robotics, behavior modeling, and real-time interaction systems.
Dávid Szabó is a habilitated Associate Professor at the Institute of Romance Studies , Department of French Language and Literature , Eötvös Loránd University. His academic profile bridges sociolinguistics , focusing on argot and slang studies in French-Hungarian contexts, with computer graphics and C# software development . He has contributed to diverse fields, including AI in education , sustainable finance , and real-time graphics APIs . Research Highlights: His work explores the intersection of language evolution and technology, with recent publications on Green Finance , AI-driven educational tools , and parallel processing in graphics programming . He investigates linguistic taboos in Hungarian politics and translation challenges of urban French slang into Hungarian, while developing educational software like StudyHelper. Technical Contributions: Szabó has pioneered the integration of modern C# with graphics APIs (Vulkan, OpenGL) for real-time rendering , creating frameworks for multi-platform applications and shader program development . His technical papers emphasize code efficiency, API abstraction, and GPU optimization.
Géza Várady is an Associate Professor at the University of Pécs (PTE), holding roles such as Vice Dean for Scientific Affairs at the Faculty of Engineering and Information Technology. He has served as Head of the Department of Technical Informatics and has held various academic leadership positions. His career spans over two decades, with research focusing on computer vision, image processing, and lighting technology. He holds a PhD from the Doctoral School of Informatics at the University of Pannonia. Education includes a Master’s degree in Computer Engineering and a PhD in Informatics. He has also held research positions internationally, such as a Leonardo Fellowship at Schefenacker GmbH in Stuttgart, Germany. His research interests include mesopic vision models, color correction systems, 3D depth sensing using monocular cameras, and drone-based applications. He leads the drone research team and has supervised doctoral students in areas like image data correction and 3D modeling. Notable achievements include the 2024 Publication Excellence Award, IBM Faculty Awards for adaptive lighting systems, and the Walsh Weston Award for contributions to lighting science. He actively participates in academic governance, serving on national committees like the Hungarian Academy of Sciences’ Engineering Sciences Committee and the John von Neumann Computer Society. Publications span over 100 articles in journals like Lighting Research and Technology and Technical Gazette , focusing on topics ranging from photogrammetry to autonomous drone control. He has authored textbooks on MPI programming and computer architecture.
