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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 .

• Machine Learning
• Smart Cities
• Mobile Computing
• +7 more

Dr. Tamás Koltai is a Professor and Dean at the Faculty of Economics and Social Sciences of Budapest University of Technology and Economics (BME). He leads the doctoral school's Specialization Group in Production Management. His roles include overseeing academic programs and research in production management, operations research, and efficiency analysis. Education: Doctor of the Hungarian Academy of Sciences (2016) Dr. habil. (2000), Budapest University of Technology and Economics Candidate of Technical Sciences (1987), Hungarian Academy of Sciences M.Sc. in Mechanical Engineering (1983), BME Faculty of Mechanical Engineering Research Interests: Dr. Koltai focuses on production management optimization, including the application of Data Envelopment Analysis (DEA), sensitivity analysis in mathematical models, and the integration of robotics in assembly lines. His work bridges theoretical models (e.g., MILP/CP optimization) with practical industrial challenges, particularly in healthcare efficiency and educational management. Notable Awards: IEOM Society Teaching Excellence Award (2021) BME GTK Faculty Memorial Medal (2016) János Susánszki Award (2013) Széchenyi Professorship Scholarship (1999–) Teaching & Leadership: He has held visiting roles at the University of Seville (1990–1992) and the University of Michigan (1988/89). His teaching excellence is recognized through awards and his contributions to business simulation education. His research often collaborates with industry partners to address real-world operational challenges. Labs/Teams: Leads the Production Management Specialization Group and contributes to interdisciplinary teams focusing on manufacturing efficiency and healthcare operations within BME.

• Production Management
• Operations Research
• Data Envelopment Analysis (DEA)
• +3 more

Miklós Koren is a Professor of Economics at the Central European University (CEU), Vienna. He serves as Head of the MS in Business Analytics Program and a Core member of the Economics Doctoral School. His research focuses on international trade, economic development, and the role of management in economic growth. He holds a Ph.D. from Harvard University (2005), an M.A. from CEU (2000), and a B.A. from Corvinus University Budapest (1999). Education: Ph.D. in Economics, Harvard University, 2005 M.A. in Economics, Central European University, 2000 B.A. in Economics, Corvinus University Budapest, 1999 Research Interests: Dr. Koren’s work examines the impact of managerial practices on economic development, trade policies, and firm performance. He has explored topics such as the effects of international experience on managerial talent, the role of expatriate CEOs in enhancing productivity, and the long-term implications of social distancing on industries reliant on face-to-face interactions. His research integrates empirical analysis with theoretical frameworks, often using large datasets to address questions of economic volatility and diversification. Key Contributions: He leads the CEU MicroData research group and has received an ERC Starting Grant for his work on trade and development. His publications span journals like the Quarterly Journal of Economics and PLoS ONE, addressing issues ranging from managerial skills in post-communist economies to the predictive power of machine learning in geospatial flows. Awards: Recipient of the Peter Kenen Fellowship and the Nicholas Káldor Prize, recognizing his contributions to economic theory and applied research. Grants & Labs: His research has been supported by grants from the European Research Council. He contributes to the development of research tools like the Stata package 'eventbaseline' for event study analysis.

• International Trade
• Economic Development
• Labor Economics
• +4 more

Prof. Zoltán Károly Lakner is a Professor at the Hungarian University of Agriculture and Life Sciences, affiliated with the Department of Agricultural and Food Economics. His research focuses on applying dynamic systems theory, econometrics, and artificial intelligence to analyze food supply networks, agricultural policy, and socio-economic systems in Africa and Central Asia. Key areas include big-data modeling of complex systems, game-theory applications, and open-source intelligence tools in innovation policy. He leads the SafeConsume H2020 project, developing strategies to mitigate foodborne illness risks through consumer education and prototype tools. His work spans food policy analysis, climate change impacts on agriculture, and ethical food consumption behaviors. Education details not explicitly provided in text. Research interests emphasize quantitative methods in agricultural economics, econometrics-driven policy analysis, and interdisciplinary approaches to global food challenges. Recent publications explore bioenergy expansion effects, water tax policy implications, and post-Paris Agreement green finance trends. No scientific awards explicitly stated in the text. Grants include the Horizon 2020 SafeConsume project. Active in advising and mentoring, though specific student names are not listed. Affiliated with the Szént István Campus in Gödöllő, contributing to institutional research and policy initiatives.

• Agricultural Economics
• Food Policy
• Policy Analysis
• +3 more

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.

• Cyber Security
• Networked Embedded Systems
• Internet of Things (IoT) Security
• +7 more

Miklós Szócska is a Professor and Dean of the Faculty of Public Health at Semmelweis University, Budapest. He also serves as the Director of the Healthcare Management Training Center and Head of the Institute of Digital Health Sciences. His career bridges academic leadership with healthcare policy, including roles as Secretary of State for Health (2010–2014), where he focused on evidence-based health policy, public health taxes, and e-health systems. Education: General Practitioner, Semmelweis University (1989) Master of Public Administration, Harvard University's John F. Kennedy School of Government (1998–1999) PhD, Semmelweis University (2008) Research Interests: Szócska's work spans network analysis , leadership and change management , crisis communication , social innovation , and big data/AI applications in healthcare . His recent studies focus on reconstructing 3D histological structures via machine learning, global mortality linked to pathogens, and tobacco control policies. Article Trends: His publications emphasize global health metrics (e.g., mortality decomposition, colorectal cancer risk factors) and digital health innovations (AI, e-health). Systematic analyses from the Global Burden of Disease Study frequently inform his research. Academic Affiliations: He leads the Institute of Digital Health Sciences and chairs the Faculty of Public Health at Semmelweis University. His international roles include Board Membership at the European Health Forum Gastein and Supervisory Board positions at EIT Health.

• Healthcare Management
• Network Analysis
• Leadership and Change Management
• +6 more

Márk Jelasity is a Full Professor in the Department of Algorithms and AI at the University of Szeged, Hungary, where he has been working since 2016. Previously, he served as a research advisor (equivalent to full professor) and senior research scientist at the Research Group on Artificial Intelligence (RGAI) of the Hungarian Academy of Sciences. His career includes numerous international research positions at institutions in Sweden, Norway, France, Italy, and the Netherlands. Professor Jelasity's research spans distributed systems, peer-to-peer computing, gossip protocols, and decentralized machine learning. His work bridges theoretical foundations with practical applications, particularly in the areas of self-organizing systems and privacy-preserving computation. His research has significant implications for smart grid technologies, secure distributed systems, and robust machine learning. His publication record shows a clear evolution from foundational work in gossip protocols and peer-to-peer systems toward cutting-edge research in decentralized machine learning, adversarial robustness, and privacy-preserving AI. Recent publications demonstrate his leadership in comparing gossip learning with federated learning approaches and exploring novel techniques for enhancing robustness in neural networks. Bolyai Plaquette (2015) 10 years best paper award at ACM/IFIP/USENIX Middleware Conference (2014) Best paper award at IEEE International Conference on Peer-to-Peer Computing (2014) Best paper award at IEEE International Conference on Self-Adaptive and Self-Organizing Systems (2013) Scientific Award of the Faculty of Science and Informatics, University of Szeged (2013) Fulbright Scholarship to visit Cornell University (2013) Multiple Bolyai Scholarships (2007-2014) Professor Jelasity has been actively involved in the academic community as an organizer of major conferences including DAIS'16 (TPC co-chair), SASO 2010 (General Co-Chair), and SASO 2007 (TPC co-chair). His leadership in the field is evidenced by his extensive publication record in top venues and his role in editing special issues and conference proceedings.

• Distributed Systems
• Peer-to-Peer Computing
• Gossip Protocols
• +7 more

Andrea Kő is a researcher at the Corvinus University of Budapest's Institute of Data Analysis and Informatics, with a focus on artificial intelligence, fintech, and big data applications. She has held positions in the Department of Information Systems until 2022 before transitioning to her current role. Her work emphasizes investment recommenders, Industry 4.0 readiness, and e-government solutions. Her research spans financial technologies, manufacturing optimization, and organizational resilience in SMEs. Notable contributions include hybrid AI models for production systems and frameworks for digital transformation assessment. She actively contributes to international conferences like EGOVIS and BiDEDE, editing proceedings and presenting on topics such as robo-advisors and smart manufacturing. Key projects include the CCMS2.0e maturity model for Industry 4.0 adoption and studies on pandemic impacts on SMEs. Her work integrates machine learning (ANFIS, MMNN) with domain-specific challenges, addressing both theoretical and practical aspects of digital innovation across sectors.

• Artificial Intelligence
• Fintech
• Big Data
• +3 more

János Kertész is a Professor at the Department of Network and Data Science at Central European University (CEU) since 2012, and previously held the position of Professor at the Budapest University of Technology and Economics (1992–2018). He obtained his PhD in Physics from Eötvös University (1980) and DSc from the Hungarian Academy of Sciences (1989). His research spans statistical physics applications, complex networks, and financial analysis. He has authored over 280 papers and served on editorial boards of journals like Journal of Physics A and Physical Review E . His research focuses on interdisciplinary topics including social network dynamics, systemic risk in economic systems, and algorithmic bias in digital environments. Notable awards include the Széchenyi Prize (Hungary’s highest scientific honor) and the Finland Distinguished Professorship. He has led projects such as SAI (Socially Explainable AI) and HUMANE-AI-NET, addressing algorithmic bias and AI ethics. His work bridges physics-based modeling with real-world social and economic systems, emphasizing computational approaches to corruption, opinion formation, and innovation diffusion. Key contributions include modeling cascading failures in interdependent networks and analyzing attention dynamics on platforms like Sina Weibo during the pandemic. He advises on systemic risk mitigation strategies and collaborates internationally, with visiting roles in Germany, the U.S., France, Italy, and Finland.

• Statistical Physics
• Complex Networks
• Financial Analysis
• +9 more

András Perczel is a Professor at the Department of Organic Chemistry, Eötvös Loránd University (ELTE), Faculty of Science, and a Full Member of the Hungarian Academy of Sciences. He holds additional roles as a lecturer in the Institute of Chemistry and has been awarded the honorary title Doctor et Professor Honoris Causa. His research focuses on peptide synthesis, protein structure and dynamics, amyloid formation mechanisms, and drug discovery, with particular emphasis on KRAS inhibitors and biotechnological applications. Key research interests include the development of sustainable peptide synthesis methods using flow chemistry and machine learning, structural studies of amyloid polymorphism, and the design of functional proteomimetics. He has contributed to understanding the molecular basis of protein aggregation in diseases and advancing analytical techniques for peptide characterization. His publications highlight advancements in amyloid core interfaces, GLP-1 receptor agonists, and the application of chiral spectroscopy in protein stability analysis. Scientific awards include membership in the Hungarian Academy of Sciences and an honorary doctoral title. Dr. Perczel collaborates on projects involving KRAS-G12C inhibitors, SARS-CoV-2 nanobody design, and the synthesis of small protein domains via automated flow chemistry. His work bridges organic chemistry, biochemistry, and biotechnology, with a focus on translational research in healthcare and sustainability.

• Organic Chemistry
• Peptide Synthesis
• Protein Structure and Dynamics
• +5 more

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.

• Model-Driven Engineering
• Internet of Things (IoT)
• Software Obfuscation
• +7 more

Edina Robin is a Habilitated Associate Professor at the Institute of Language Mediation , part of Eötvös Loránd University . She serves as the Director of the Institute and leads two departments: the Department of Translation and Interpreting and the Department of Hungarian as a Foreign Language . Her work bridges theoretical and applied translation studies, emphasizing modern challenges in language mediation. Role: Director of Institute of Language Mediation Role: Head of Department of Translation and Interpreting Role: Head of Department of Hungarian as a Foreign Language Research Interests Translation universals and revision practices Corpus-based translation analysis Human-in-the-loop machine translation systems Ethical implications of AI in translation Distance education methodologies in translation training Publication Trends reflect her interdisciplinary focus on machine translation (33%), translation teaching (25%), corpus linguistics (20%), and crisis communication (15%). Recent works explore the intersection of artificial intelligence, human agency, and ethical frameworks in language mediation. Academic Leadership includes institutional development for language mediation, curriculum design for Hungarian as a foreign language, and fostering collaboration between academic and industry translation practices.

• Translation Studies
• Corpus Linguistics
• Machine Translation
• +5 more

Imre Salma is a Professor at the Department of Analytical Chemistry within the Faculty of Science at Eötvös Loránd University (ELTE). His research focuses on atmospheric chemistry, aerosol physics, and environmental science, with an emphasis on particle formation, air quality, and health impacts. He holds a Doctor of Science (DSc) degree and has extensive experience in analytical techniques, including eddy accumulation and convolutional neural networks for particle detection. Salma’s work examines ultrafine particles in urban environments, investigating their sources, dynamics, and health consequences. His research spans long-term data analysis (e.g., 11-year datasets), lockdown effects on pollution, and regional comparisons across Europe. He also explores oxidative potential of particles, lung deposition mechanisms, and firework-related air quality degradation. Key applications include improving air quality monitoring, informing policy, and advancing climate models. His publications span aerosol nucleation mechanisms, hygroscopic properties, and interdisciplinary approaches bridging chemistry, computer science, and public health. Salma collaborates internationally, contributing to initiatives like the COST Action 633. His lab is located at the Institute of Chemistry in Budapest, with a focus on cutting-edge analytical methods and environmental problem-solving.

• Atmospheric Chemistry
• Environmental Science
• Air Pollution
• +4 more

Dr. BARANYA Sándor is an Associate Professor and Head of the Department of Hydraulic and Water Resources Engineering at the Budapest University of Technology and Economics, Faculty of Civil Engineering. He holds key administrative roles, including Faculty Council Representative, Chairman of the Economic Committee, and Erasmus Committee Member. His office is located in Building K, Room MF 19, and he can be contacted via email or phone. His research spans sediment transport , river morphology , microplastic pollution , and computational fluid dynamics (CFD) . He employs innovative methods such as acoustic mapping, machine learning, remote sensing (Sentinel-2, Landsat), and numerical modeling to study large river systems, particularly the Danube. His work addresses ecological impacts, including thermal pollution from power plants and microplastic distribution. Recent publications (2023–2025) focus on: Sediment-microplastic dynamics using integrated field-data and AI Historical river regulation impacts CFD-based restoration strategies Advanced monitoring techniques (e.g., acoustic velocimetry, deep learning for riverbed analysis) He teaches courses including Hydraulics , Hydromorphology , and Water Utilisation & Damage Prevention , and mentors students in TDK (Research Society) projects on sediment transport, river habitats, and microplastics. He participates in EU initiatives like DanubeSediment for transnational sediment management.

• Sediment Transport
• River Morphology
• Microplastic Pollution
• +2 more

Tamás Tettamanti is a Professor at Budapest University of Technology and Economics, serving as Deputy Head of the Department of Control for Transportation and Vehicle Systems. He holds a PhD (2013), Habilitation (2023), and DSc (2023) in Transportation Engineering, with expertise in road traffic modeling and control. 2007–2010: PhD Student 2010–2013: Assistant Lecturer 2014–2018: Senior Lecturer 2019–2024: Associate Professor 2025–present: Full Professor Education: High School Graduation (2001), DEUG (2004), MSc in Transportation Engineering (2007), Jazz Trumpet Graduate (2008) PhD (2013), Habilitation (2023), DSc (2023) Research focuses on road traffic modeling, intelligent transportation systems (ITS), autonomous vehicle integration, and emission-aware traffic control. His work bridges theoretical developments with real-world applications, including wireless traffic light systems and deep learning for urban mobility peaks. Scientific Awards: BME PhD Research Prize (2012) Literary Awards from Hungarian Scientific Association for Transport (2013, 2017, 2021, 2023) Bolyai János Research Scholarship (2017–2020) Michelberger Master Prize (2022) BME Jubilee Medal (2023) He has led major projects such as Dynamic Adaptive Traffic Control Services (2020–2024) and Deep Learning Anticipated Urban Mobility Peaks (DARUMA) (2021–2024), with industry collaborations including Google-BME Traffic Lab.

• Road Traffic Control
• Intelligent Transportation Systems
• Traffic Simulation
• +3 more