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 .
Judit Bodnar is a Professor in the Department of Sociology and Social Anthropology at Central European University (CEU), affiliated with the Doctoral School of History. Her research spans urban theory, political economy of globalization, public space, and the cultural dimensions of capitalism. She actively contributes to academic discourse through publications and editorial roles. Research Interests: Urban theory and history Modernity and capitalism (comparative and historical) Uneven development Public space and public art Political economy and culture of globalization Sharing economy and digital platforms Food and politics Her recent work focuses on the transformation of public and private boundaries in the context of digital platforms like Airbnb and home restaurants, as well as the racial and spatial segregation of Roma communities in urban Europe. She critically examines the legacies of 1968 as a global moment and the gentrification of urban spaces such as Chicago’s Cabrini Green. The publication trends reflect a deep engagement with urban sociology, political economy, and cultural critique, especially in the context of neoliberalism, digital transformation, and global inequality. Her work bridges historical analysis with contemporary urban challenges. Editorial Role: Co-editor, Critical Historical Studies , University of Chicago Press Academic Events: Privacy Goes Public: Airbnb, Home Restaurant and the Reconfiguring of Public and Private in the Sharing Economy (November 24, 2021) Racial Cities: The Segregation of Roma in Urban Europe (October 5, 2017) She advises doctoral students in the Doctoral School of History and supervises research on urban and historical sociology. Her work is supported by interdisciplinary collaborations and engagement with global scholarly networks. She is involved in critical urban research, often linking theory with social justice concerns. Labs and Research Groups: Active participant in urban sociology and globalization research clusters at CEU Contributor to transnational dialogues on the right to the city and urban commons
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.
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.
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.
Balazs Vedres is a **Professor** at the **Central European University (CEU)**, with a joint appointment in the **Department of Network and Data Science**. His research integrates network science, data science, and social theory to explore creativity, innovation, and historical processes in collaborative networks. He holds a **PhD in Sociology from Columbia University** and an **MA in Economics from Corvinus University**. **Research Interests**: Focuses on structural dynamics in creative fields (e.g., jazz, video games, open-source software), gender inequality in collaborative platforms, historical network evolution, and the impact of social bots on human collaboration. He analyzes how network configurations like *structural folds* and *forbidden triads* drive innovation and creativity. **Awards**: Elected **Member of the European Academy of Sociology (2017)**, recognizing his contributions to sociological research. His work bridges computational methods with sociological theory, as seen in his publications in *American Journal of Sociology* and interdisciplinary journals. **Projects**: Leads initiatives like *Gendered Creative Teams: From Marginality to Success* and *Ceunet/Indra Mapping European Network Science*. His research often involves empirical studies of transnational activism, entrepreneurial networks, and digital platforms. **Labs/Teams**: Active in CEU’s **Data and Network Dynamics Studies (DNDS)** group, fostering interdisciplinary collaboration in computational social science. His work emphasizes the interplay between global economic integration and local developmental agency.
Anna Berg is an Assistant Professor in the Department of Sociology and Social Anthropology at Central European University (CEU), where she conducts research at the intersection of political sociology, cultural sociology, and media studies. Her work critically examines how digital communication practices shape political identities and mobilizations, with a focus on right-wing and populist movements in Germany. Her educational background includes a PhD in Sociology from the University of Chicago, an MA from École des Hautes Études en Sciences Sociales (EHESS) in Paris, and a BA in Political Sciences from Freie Universität Berlin. Anna's research interests include: Political and cultural sociology Media and communication in populist movements Digitalization and political identity Ethnographic studies of anti-refugee and anti-lockdown protests Youth political engagement and media practices Alternative media ecologies and disinformation Her recent publications explore themes such as informational activism, epistemic trust, political meaning-making, and the cultural dynamics of echo chambers and post-truth discourse. Using ethnographic and qualitative methods, her work moves beyond buzzwords to offer grounded sociological insights into contemporary political transformations. She is currently conducting fieldwork on media practices among high-school students, extending her inquiry into the next generation of political subjectivities. Anna has not been listed with any scientific awards or fellowships in the provided text. She advises emerging scholars through her ongoing research projects and supervises fieldwork, though specific students are not named. Her research is supported by ethnographic fieldwork and institutional affiliation with CEU, enabling long-term studies in Germany. Her work is conducted through independent research and collaboration within the Department of Sociology and Social Anthropology at CEU, contributing to broader academic discussions on democracy, representation, and digital culture.
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.
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.
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.
Dr. András Pályi is an Associate Professor at the Department of Theoretical Physics, Budapest University of Technology and Economics, and Head of the HUN-REN-BME-BCE Quantum Technology Research Group. His work bridges quantum computing, spintronics, and condensed matter physics, focusing on spin-phonon interactions, topological quantum systems, and semiconductor nanostructures. Quantum Computing Spintronics Topological Insulators Quantum Materials Recent publications highlight his research on quantum error correction , spin qubit control , non-Abelian Berry phases , and Weyl point stability , with applications in nanomechanical resonators and Majorana qubit architectures. His group explores spin-orbit coupling, acoustic phonons, and lattice reorientation mechanisms in quantum systems. Contact: Office F III. mfszt 6, palyi.andras@ttk.bme.hu , +36 1 463 4109
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.
Gabor Simonovits is an Associate Professor in the Department of Political Science at Central European University (CEU), with affiliate roles in the Undergraduate Studies and the Doctoral School of Political Science, Public Policy, and International Relations. He holds a PhD in Politics from New York University (2018), an MA in Politics from Stanford University, an MA in Economics from CEU (2011), and a BA in Applied Economics from Corvinus University. His research bridges substantive and methodological inquiry in public opinion studies, focusing on attitudes toward public policies in the U.S., inter-group prejudice in Hungary, and quantitative methods addressing researcher incentives in experimental studies. Simonovits teaches courses on research methods and political behavior at CEU. His work appears in top journals such as Science, the American Political Science Review, and the American Journal of Political Science. He has conducted field experiments on discrimination in housing and ride-sharing platforms, analyzed federalism and abortion law dynamics post-Dobbs, and explored communication strategies in political scandals. His methodological contributions address publication bias and experimental design transparency. Notable collaborations include interventions to reduce anti-Roma discrimination in Hungary’s rental market and studies on democratic erosion’s psychological underpinnings. Simonovits has organized departmental seminars on topics ranging from substance use regulation to electoral autocracy campaigning. His research emphasizes bridging empirical rigor with real-world policy implications, particularly in contexts of democratic backsliding and social inequality.
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.
Zoltán Sütő is an Associate Professor at the Budapest University of Technology and Economics, affiliated with the Department of Automation and Applied Informatics. His research focuses on advanced power electronics and control systems, with expertise in real-time implementation using FPGA technology. He maintains an active presence through institutional contacts at Budapest 1117, Magyar tudósok krt. 2., Q.B114, and can be reached via phone (+36 1 463-2337) or email (Suto.Zoltan@aut.bme.hu). Dr. Sütő's research encompasses: Design and optimization of power converters (dual active bridge, multilevel inverters) Real-time control algorithms for grid-connected systems and microgrids FPGA-based hardware-in-the-loop simulation methodologies Nonlinear dynamics in power electronic systems Artificial intelligence applications for fault diagnosis in drive systems His work bridges theoretical control models with practical implementations in renewable energy integration and power quality management. Recent publications demonstrate a strong focus on predictive control techniques, adaptive compensation methods, and optimization of power converter topologies. Research trends emphasize real-time validation, FPGA implementation, and AI-enhanced diagnostics across applications ranging from energy storage systems to industrial drives. Articles consistently address efficiency improvements, stability challenges, and novel modulation strategies in power conversion.
