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Dr. HAJNAL Géza is an Associate Professor at the Budapest University of Technology and Economics (BME), Faculty of Civil Engineering, where he serves in the Department of Hydraulic and Water Resources Engineering. His office is located in Room K. ép / mf. 12/7, and he can be contacted via email at hajnal.geza@emk.bme.hu or phone at +36 1 463 2362. His teaching portfolio includes active courses such as Hydraulic Engineering, Water Management (BMEEOVVAT43) and Hydrometric Field Course (BMEEOVVAI44). Previously, he taught Hidrogeology (BMEEOGMMET3) and Hydrogeology of Subsurface Water (BMEEOGMDT81). HAJNAL's research specializes in hydrogeology , with emphases on karst aquifer dynamics, groundwater flow modeling, climate impacts on hydrology, and hydraulic engineering. His work integrates field measurements (e.g., drip-water monitoring in Buda Castle Cave) with advanced numerical modeling to address complex hydrological challenges in Hungarian watersheds. Analysis of his 15 most recent publications (2013–2025) reveals dominant themes: 73% focus on karst/fractured aquifers , 20% on hydrological modeling techniques , and 7% on socio-environmental conflicts. Recurrent technical subfields include seepage flow validation, transmissivity determination, and rainfall-runoff sensitivity. No scientific awards, grants, student advisees, or lab affiliations are documented in the provided materials.

• Hydrogeology
• Karst Aquifers
• Groundwater Flow Modeling
• +3 more

Katalin Piniel is an Assistant Professor at the Department of English Applied Linguistics within the School of English and American Studies at Eötvös Loránd University, Budapest. Her work bridges applied linguistics and educational psychology , focusing on the dynamic interplay of emotions , including language anxiety , motivation, and self-efficacy in foreign language learning contexts, particularly in Hungary. PhD in Language Pedagogy (ELTE) Associate Editor of Studies in Second Language Learning and Teaching Active reviewer for applied linguistics journals Her research integrates complex dynamic systems theory to analyze longitudinal changes in affective variables and employs meta-analytic techniques to validate anxiety measurement tools like the Foreign Language Classroom Anxiety Scale (FLCAS) . She explores formative and summative assessment practices in Hungarian high schools and investigates flow experiences during language tasks. Her methodological interests include quantitative tools (e.g., Rasch analysis), collaborative research , and cross-cultural comparisons (e.g., Hungarian-Kazakh studies). Recent publications highlight trends in emotion-motivation dynamics , skills-based anxiety measurement , and the impact of online education on affective variables. She collaborates on projects examining special needs learners , including Deaf and hard-of-hearing students , in foreign language acquisition. Contact: brozik-piniel.katalin@btk.elte.hu | ORCID | Google Scholar | ResearchGate

• Applied Linguistics
• Language Learning
• Emotions in Education
• +5 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

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

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.

• Network Science
• Complex Systems
• Computational Social Science
• +8 more

Miklós Tibor Horváth is a Professor at the Department of Mathematics , Budapest University of Technology and Economics , specializing in inverse spectral problems and differential operators. He serves as Head of Department and holds the MTA doktora degree. Email: horvath@math.bme.hu Office: H226c Phone: +36-1-463-2630 Research Interests: His work focuses on inverse spectral theory, including reconstruction of linear differential operators from spectral data, eigenvalue distribution of Sturm-Liouville problems, and fixed-energy inverse scattering. Key areas include stability analysis of inverse problems and closed exponential systems. Publications & Teaching: Horváth has published extensively in journals like Inverse Problems and Transactions of the American Mathematical Society , with notable contributions to stability theorems and spectral shift functions. He teaches courses such as Analysis 2 , Functional Analysis , and Inverse Distribution Problems at both undergraduate and graduate levels. Additional Information: Personal Website: http://math.bme.hu/~horvath Mathscinet Profile: AMS Profile Google Scholar: Google Scholar Profile

• Inverse Spectral Problems
• Sturm-Liouville Operators
• Inverse Scattering Theory
• +3 more

Horváth Miklós Tibor is a University Professor at the Department of Mathematics, Budapest University of Technology and Economics. His research focuses on inverse spectral problems for linear differential operators, particularly Schrödinger and Dirac operators, and topics such as inverse scattering theory and eigenvalue distribution. Research Interests: Inverse spectral problems, Schrödinger operators, Sturm-Liouville theory, inverse scattering, measure theory. Teaching: Courses include Analysis 2, Functional Analysis, and Distribution Theory. Contact: horvath@math.bme.hu

• Inverse Spectral Problems
• Linear Differential Operators
• Schrödinger Operators
• +3 more

Dr. Farkas-Karay Gyöngyi serves as Assistant Professor at the Department of Hydraulic and Water Resources Engineering within the Faculty of Civil Engineering at Budapest University of Technology and Economics (BME). She teaches core courses including Groundwater (BMEEOVVMV63), Hydrogeology (BMEEOGMMG62), and Hydraulic Engineering, Water Management (BMEEOVVAT43), maintaining office hours Fridays 10:00-12:00 in room K. ép / mf. 12/7. Education: Civil Engineering BSc (2011) Structural Engineering MSc (2013) PhD (2018) Research Focus: Her expertise centers on fractured and karst aquifer systems, conducting hydraulic investigations of complex rock formations, developing methodologies for pumping test evaluation in fractured media, and implementing numerical models for groundwater flow characterization. This work bridges theoretical hydrogeology with practical water resource management applications. Publication Trends: Analysis of her 2013-2017 publications reveals consistent advancement in fractured/karst aquifer characterization techniques. Key contributions include non-linear flow analysis in pumping tests, transmissivity determination from mining operations, and integrated physical-numerical modeling approaches. Her research demonstrates strong methodological rigor across laboratory experiments, field data interpretation, and computational simulation. Scientific Awards: No awards documented. Advising and Grants: Available materials contain no information regarding student supervision, research grants, or funded projects.

• Hydrogeology
• Groundwater Hydrology
• Fractured Rock Hydrology
• +3 more

Péter Szigetvári is an Associate Professor at the School of English and American Studies , Eötvös Loránd University , specializing in the Department of English Linguistics . His work bridges phonology, morphology, and theoretical linguistics, with a focus on Hungarian and English language structures. Academic Rank: Associate Professor Department: Department of English Linguistics University: Eötvös Loránd University His research explores phonological patterns , including vowel harmony, syllable structure, and morphological constraints. He investigates the interplay between morphology and phonology in Hungarian and English, analyzing phenomena like diminutive formation, diphthong debates, and stress-related vowel reduction. Recent publications highlight trends in Vowel Harmony , Syllable Typology , and Morpho-Phonological Variation . His work often challenges traditional frameworks, proposing paradigm-based or VC phonology approaches. Péter Szigetvári's professional activities include contributions to linguistic journals and a blog at nyest.hu . His office is located at Room 302, Rákóczi út 5, Budapest (1088).

• Linguistics
• Phonology
• Morphology
• +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

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.

• Internet of Things
• Mobile Robotics
• Wireless Sensor Networks
• +5 more

Dr. TÓTH Csaba is an Associate Professor at the Department of Highway and Railway Engineering, Budapest University of Technology and Economics (BME), Faculty of Civil Engineering. He teaches courses such as Highway and Railway Structures (BMEEOUVAI41) and Pavement Structures (BMEEOUVMU63), while previously teaching Pavement Analysis and Design (BMEEOUVDT81) and Project Management in Transportation (BMEEOUVMU-4). His research focuses on asphalt technology, pavement diagnostics, and sustainable road construction. Phone: +36 1 463 1154 Room: ÉL. ép / 206/E Research Interests: His work emphasizes non-destructive evaluation methods (e.g., Ground-Penetrating Radar), rheological modeling of asphalt binders, recycled asphalt pavement applications, and climate-adapted pavement design. Key methodologies include the Ramberg-Osgood model for dynamic modulus prediction and the virtual inertial point method for structural diagnostics. Scientific Contributions: Recent research trends highlight sustainable road rating systems, thermal stress analysis in asphalt pavements, and advanced diagnostic techniques for infrastructure monitoring. Scientific Awards: Magyar Felvételi Scholarship (#építő250)

• Road Engineering
• Railway Engineering
• Asphalt Technology
• +3 more

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.

• Information spreading
• Agent-based simulations
• Cellular automata
• +1 more

Yusaf Akbar is a Professor at the Department of Economics and Business at Central European University (CEU). His research focuses on business strategy, public policy, and emerging markets, particularly the sharing economy and non-market strategies. He has held research fellowships at the Institute for Advanced Study and visiting roles at the University of Trieste and Wirtschaftsuniversität Wien. His work bridges academic research with practical applications, including advising the European Commission and multinational corporations like Accenture and Siemens. Education: DPhil in Economics from the University of Sussex (2000). Key publications include EU Enlargement and Central Europe: Regulatory Convergence and the Multinational Enterprise and Global Antitrust: Trade and Competition Linkages . Upcoming books include Digitalization in Emerging Markets (Cambridge University Press, 2024) and an edited volume on emerging markets research agendas (Edward Elgar, 2025). Research interests emphasize strategic calibration in complex environments, AI-augmented decision-making, and systemic vulnerability management. He advises global firms on non-market strategies and has authored case studies for companies like ING Insurance, Vienna International Airport, and Hummus Bar. Professional roles include Founding Editor of the International Journal of Emerging Markets and Editorial Advisory Board member for Journal of Asia-Pacific Business . Teaching spans universities worldwide, including University of Michigan, Stockholm School of Economics, and Queen’s University.

• Business Strategy
• Public Policy
• Sharing Economy
• +5 more

Sándor Ádány is a Professor at the Department of Structural Mechanics , Budapest University of Technology and Economics. His work focuses on advanced structural analysis of thin-walled members and systems-based design methodologies. Research Interests: Specializes in buckling behavior of thin-walled structures, finite element modeling, cold-formed steel stability, and modal decomposition techniques. Key areas include Lateral-torsional buckling Displacement mapping in constrained FEM Stiffener optimization in plate structures Combined loading stability of tubular members Prebuckling deformation effects Fourier-based numerical methods Article Trends (2023-2025): Recent publications emphasize elastic stability analysis of thin-walled beams and tubular structures under complex loading conditions, with particular attention to prebuckling deflections, torsional rigidity effects, and numerical validation of analytical models. Innovations include Fourier-series displacement approximations and constrained finite element methodologies.

• Structural Engineering
• Computational Mechanics
• Finite Element Modeling
• +3 more