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 .
Dr. Gábor Pintér holds dual academic appointments as Assistant Professor at Károli Gáspár Reformed University's Faculty of Humanities and Social Sciences (Department of Japanology) and as Associate Professor at Kobe University's School of Languages and Communication. Born in Hungary in 1977, he earned his MA (2005) and PhD (2008) in Linguistics from Kobe University, Japan, with a dissertation on asymmetrical segment distributions in Japanese. His research focuses on three interconnected domains: phonological theory (especially Japanese phonology), experimental phonetics, and applications of automatic speech recognition in language education. Specific interests include vowel devoicing patterns, prosodic perception in L2 learners, phonotactic constraints, and diachronic sound changes in Japanese. Pintér actively contributes to international research collaborations, including the JSPS-funded project 'Stochastic & theoretical phonological research' and serves as chair of the Phonology Association in Kansai (PAIK). His 15 most recent publications demonstrate methodological diversity, combining theoretical linguistics with computational approaches and experimental studies, primarily focused on Japanese phonetics and speech technology applications. Professional memberships include board positions in The Phonological Society of Japan and memberships in the International Speech Communication Association and Association for Laboratory Phonology.
Roles: Full Professor at Budapest University of Technology and Economics (BME), leading the Laboratory of Cryptography and Systems Security (CrySyS Lab) . Specializes in cyber security, IoT security, and privacy technologies. Served as Associate Editor for IEEE Transactions on Mobile Computing and Elsevier Computer Communications. Education: M.Sc. in Computer Science, BME (1995) Ph.D. in Computer Science, Swiss Federal Institute of Technology Lausanne (EPFL, 2002) Habilitation at BME (2013) Doctor of Science, Hungarian Academy of Sciences (2021) Research Interests: Focuses on malware detection on embedded systems, security of industrial control systems, and privacy-preserving AI. Current projects include DOSS (IoT supply chain security), SECURED (health data security), and SPAM (AI and cybersecurity). Published over 150 papers and co-authored books on wireless network security and cryptographic obfuscation. Grants & Awards: Awarded Dennis Gabor Award (2024), Bolyai Fellowship (2008-2011), and led EU projects like SEVECOM and WSAN4CIP. Current grants include H2020 DOSS and OTKA-funded research on federated learning incentives. Advising: Supervised 13 PhD students, including current faculty members (e.g., András Gazdag, Dorottya Papp). Active in mentoring CTF teams like !SpamAndHex (DEFCON qualifier). Labs & Teams: Director of CrySyS Lab, leading research in embedded device security, vehicle cyber defense, and industrial IoT resilience. Active in EDIH cybersecurity consulting for SMEs.
Federico Battiston is an Associate Professor of Network Science and Director of the PhD Program in Network Science at Central European University (CEU), the first such program in Europe. He holds a PhD in Applied Mathematics from Queen Mary University of London and degrees in statistical physics from Sapienza University of Rome. His research focuses on network science, complex systems, and computational social science, with contributions in leading journals like Nature Physics , Physical Review Letters , and Science Advances . He coordinates the software project Hypergraphx and was Chair of NetSci2023, the largest Network Science conference. He has received awards including the Complex Systems Society's Junior Award (2022) and the European Physical Society's Early Career Prize (2021). Education: PhD in Applied Mathematics, Queen Mary University of London MSc in Theoretical Physics, Sapienza University of Rome BSc in Physics, Sapienza University of Rome Research Interests: Battiston explores generalized network structures (e.g., multilayer and higher-order networks), dynamics on networks (epidemics, social/cultural dynamics, synchronization), and their applications in social systems, neuroscience, and ecology. He emphasizes how network topology influences collective behavior and emergent phenomena. Key Contributions: His work includes hypergraph modeling, collaboration in escape rooms, and the role of higher-order interactions in brain networks. He co-authored the book Higher-order systems and guest-edited a Focus Collection on higher-order networks in Communications Physics . Awards & Roles: Junior Award of the Complex Systems Society (2022) Early Career Prize, European Physical Society (2021) Elected Member, Complex Systems Society Council Editor, Communications Physics Advising & Grants: Advised PhD students such as Milan Janosov, Luis Natera, and Rebeka Szabo. Two students received CEU Advanced Awards. His projects include Mapping the Higher-Order Dynamics of Neurodegeneration and DYNASNET . Labs/Teams: Leads the Hypergraphx team and collaborates on interdisciplinary projects in network science, including ecological networks and urban mobility analysis.
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. habil. Simon János PhD is an Associate Professor at the University of Szeged's Faculty of Engineering, Institute of Technology. Born on July 27, 1980, he maintains his office at 6724 Szeged, Moszkvai krt. 9. Room F9, with contact number +36-62-546-575. His educational background includes IT engineering and electrical engineering from Technical College of Subotica (1999-2005), Certified Computer Engineering from University of Novi Sad (2005-2008), PhD in Engineering from University of Osijek (2008-2014), and habilitation from Óbuda University Doctoral School of Security Sciences (2020). English (intermediate, complex) Serbian (advanced, complex) Dr. Simon's research focuses on design and programming of Internet of Things environments, hardware and software development of mobile robots and wireless sensor networks, and analysis of Industry 4.0 case studies. His teaching portfolio includes Computer Modeling, Simulation courses, Microcontrollers, Graphical Programming at BSc level, and Real-time systems, Autonomous and intelligent robots at MSc level. He serves as Associate Editor for Analecta Technica Szegedinensia and is a member of the Higher Education Management Education Methodology Association (FIOM). His international experience includes CEEPUS mobility to Timisoara, Erasmus mobility to multiple Romanian cities, and participation in IoTTech Expo Global in London.
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.
Szandra Ésik is a Lecturer at the Department of Chinese Studies, Faculty of Humanities, Eötvös Loránd University. She teaches Chinese language and political discourse analysis while contributing to Hungarian-Chinese lexicography projects. Institute of East Asian Studies Department of Chinese Studies Research Interests: Chinese political rhetoric and discourse analysis Second language teaching methodologies for Chinese Translation studies and bilingual dictionary development Silk Road cultural/economic history Environmental policy in Chinese Communist Party congresses Her recent publications focus on comparative analysis of political speeches (2017-2020), character teaching strategies, and collaborative dictionary projects with scholars like Huba Bartos and Imre Hamar. She has contributed to institutional research at ELTE's Chinese Studies department. Contact: esik.szandra@btk.elte.hu
Dr. Balázs Varga is a Research Fellow at the Department of Control for Transportation and Vehicle Systems, Budapest University of Technology and Economics (BME). He holds a PhD in Transportation and Vehicle Sciences (2021) and an MSc in Vehicle Engineering (2015) from BME. His industry experience includes roles at AVL Hungary as a Software and Function Developer (2016–2018) and academic positions at Chalmers University of Technology (2015) and SZTAKI (2012–2014). Current Role: Research Fellow (2021–present) Teaching: Programming, Control Theory, Traffic Modeling (English language course) Research Interests: Varga specializes in road traffic modeling and control, focusing on AI-based traffic estimation and dynamic traffic management. His work integrates machine learning with mesoscopic and microscopic traffic simulation tools like SUMO to optimize urban mobility and reduce emissions. Projects: He leads the 2020–2024 national development project 'Dynamic, adaptive traffic control services and evaluation tools based on digitally connected data sources' (2019-1.1.1-PIACI KFI). This initiative leverages connected data sources for real-time traffic control and policy evaluation. Key Publications Trends: His recent articles explore topics such as graph neural networks for sensor placement, multiobjective control of emissions, and mixed-reality V2X testing. These works emphasize data-driven approaches, emission reduction, and simulation frameworks for autonomous vehicles.
Dr. Varga István is a Full Professor at the Budapest University of Technology and Economics (BME) in the Faculty of Transportation Engineering and Vehicle Engineering, and a Scientific Advisor at the HUN-REN Institute for Computer Science and Control. He holds a D.Sc. from the Hungarian Academy of Sciences (2020), a Ph.D. (2007), and an M.Sc. in Transportation Engineering (1998). His primary research focuses on road traffic control and traffic automation systems , with expertise in intelligent transportation solutions and vehicle mechatronics. His research integrates control theory with practical applications in urban mobility, including dynamic traffic light systems, autonomous vehicle impacts, and emission modeling. Recent work explores V2X communication, platooning technologies, and microscopic traffic simulation for urban optimization. He has led major projects such as the national innovation project 'Dynamic, adaptive traffic control services based on digital data sources' (2020-2024) and industrial collaborations with Knorr-Bremse, Siemens, and nuclear energy sectors. Awards include the Hungarian Academy of Sciences Young Prize (2007) and multiple recognitions for technological innovation. Educational activities include courses on Road Traffic Control, Mathematical Methods, and Vehicle System Modeling. Laboratory leadership includes the Road Traffic Control Lab with industry partnerships like Bosch and SWARCO.
Tamas Koltai is a Professor at the Budapest University of Technology and Economics, affiliated with the Department of Management and Corporate Economics within the Faculty of Economic and Social Sciences. He holds a PhD in Industrial Engineering and is actively contributing to research in operations management, production planning, and industrial engineering. His research interests include: Operations Management Industrial Engineering Production Planning Assembly Line Balancing Human-Robot Collaboration Data Envelopment Analysis (DEA) Supply Chain Management Learning Curves Flexible Manufacturing Systems Performance Evaluation His recent publications focus on applying mathematical programming models (MILP, CP), simulation, and DEA to optimize assembly lines, particularly under learning effects and human-robot collaboration. He explores workload distribution, cycle time optimization, and efficiency evaluation in both manufacturing and service sectors, including healthcare and business simulation games. His work bridges theoretical models with practical industrial applications, supporting managerial decision-making under uncertainty. While no specific scientific awards are listed, his extensive publication record (over 50 papers) and high citation count reflect significant academic impact. He frequently collaborates with researchers such as Imre Dimény, Noémi Kalló, Viola Gallina, and Rita Dénes. There is no public information on PhD students advised or grants received. His work does not mention specific labs or research teams, but his focus on applied operations research suggests strong industry collaboration potential.
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 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
Tamás Bartha serves as Associate Professor at Budapest University of Technology and Economics' Department of Control for Transportation and Vehicle Systems since 2013, following previous appointments at the Department of Measurement and Information Systems where he progressed from PhD student (1993-1996) to Assistant Professor (2001-2009) and Associate Professor (2009-2013). He concurrently holds a Senior Research Fellow position at the Institute for Computer Science and Control, MTA SZTAKI since 1998. His educational background includes an MSc in Electrical Engineering (1993) and PhD (2001) from the same institution. MSc in Electrical Engineering (1993) PhD (2001) Bartha specializes in formal verification methodologies for safety-critical systems, with particular expertise in nuclear power plant control systems. His research focuses on model checking , formal verification and validation of complex control systems , and reliability analysis of computer systems . His work bridges theoretical computer science with practical transportation and nuclear engineering applications, emphasizing fault tolerance in critical infrastructure. He leads significant projects including MTA SZTAKI's initiatives for the Paks Nuclear Power Plant, contributing to the Reactor Protection System renovation and Universal Test System development. His professional recognition includes multiple MTA SZTAKI awards and international committee memberships. IFAC Technical Committee 1.5 on Networked Systems IAEA Technical Working Group on Nuclear Power Plant Control and Instrumentation Committee on Automation and Computer Science of the Hungarian Academy of Sciences Bartha teaches specialized courses including 'Modern Automotive Products and Development Methods' and delivers formal methods lectures in 'Traffic Automation'. His industry collaborations span major transportation and engineering firms including HungaroControl, Siemens, and Robert Bosch. Fluent in English, German, and Russian, he was born in Budapest on April 22, 1969.
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.
