جست‌وجوی استاد و پژوهشگر

Jürgen Zieglerمشاهده پروفایل

استاد

• Human-Computer Interaction
• Recommender Systems
• Explainable AI
• +۹ مورد دیگر

Jürgen Ziegler is a Senior Full Professor at the Department of Computer Science and Applied Cognitive Science within the Faculty of Computer Science at the University of Duisburg-Essen. He leads the Interactive Intelligent Systems Group, focusing on human-computer interaction, recommender systems, and explainable AI. His work emphasizes transparency, user control, and interdisciplinary collaboration with industry partners. He earned his doctoral degree from the University of Stuttgart, specializing in formal user interface design methodology. Prior to his current role, he headed the Competence Center for Software Technology and Interactive Systems at the Fraunhofer Institute for Industrial Engineering (IAO) in Stuttgart. He also served as Editor-in-Chief of the journal i-com - Journal of Interactive Media from 2001 to 2021. Ziegler’s research bridges academic and industrial domains, with applications in e-commerce, health, social media, and automotive systems. He investigates how to make intelligent technologies more transparent and user-controllable, particularly in conversational recommender systems, personalized interfaces, and social media analytics. His work integrates visualization techniques and semantic data models to enhance user experience. His recent publications focus on multistakeholder evaluation frameworks, explainable AI, and the integration of conversational agents with traditional interfaces. These studies explore domains like health promotion, smart environments, and education, using methods such as knowledge graphs, generative AI, and interactive sliders for feature dependency visualization. Ziegler founded and co-chairs the German Special Interest Group on User-Centred Artificial Intelligence. He has contributed to funded projects like SPIDER, FairWays, and PAnalytics, which address polarization in social networks, interactive recommendation, and health support systems. His leadership roles include organizing international workshops on explainable user models and user-centered AI. He supervises PhD students and advises on projects related to recommender systems, mental models, and user interaction preferences. His team collaborates on multi-method approaches for transparent decision support and the development of tools for measuring user perception of recommendation transparency. Labs and teams under his direction include the Interactive Intelligent Systems Group, which develops demonstrators like AR-based shopping advisors and hybrid recommendation frameworks. His work emphasizes both theoretical advancements and practical implementations across diverse application scenarios.

• Linguistics
• German Linguistics
• Translation Studies
• +۳ مورد دیگر

Peter Csatar serves as Associate Professor and Head of the Department of German Linguistics at the Institute of Germanistics, Faculty of Humanities, University of Debrecen, a position he has held continuously since 1995. He earned his PhD from the University of Debrecen in 2000 and maintains active research and leadership roles within the department. Education: PhD, University of Debrecen (2000) Csatar's research spans the dynamic intersection of linguistic theory and sociopolitical contexts, with particular emphasis on metaphorical structures in discourse and cross-linguistic phenomena. His work demonstrates exceptional depth in German-Hungarian contrastive linguistics, migration discourse analysis, and cognitive approaches to language acquisition. Key methodological strengths include experimental linguistics for child language studies and critical discourse analysis of political terminology. Metaphor theory applied to translation and political buzzwords (e.g., 'asylum tourism') German-Hungarian comparative linguistics focusing on demonstratives and idioms Migration discourse analysis in Hungarian digital media Cognitive patterns in narrative structures and folklore His publication trajectory from 2021-2025 reveals intensifying focus on Hungarian linguistic phenomena within migration contexts, demonstrating methodological evolution from theoretical metaphor analysis toward experimental child language research and digital media discourse studies. Notable trends include the examination of translator roles in machine translation eras and systematic investigation of exophoric demonstratives in Hungarian acquisition. Scientific Awards: No scientific awards were documented in available sources. Advising and Grants: While specific grant funding and student advising details remain unreported in public profiles, Csatar's extensive co-authorship network (particularly with Eniko Toth on 14 publications) indicates active research mentoring. His departmental leadership since 1995 suggests substantial administrative oversight of academic programs. Labs and Teams: Csatar coordinates the MANYE #transpub initiative, organizing translation publishing workshops and academic events. His primary research ecosystem involves the Department of German Linguistics' metaphor and discourse analysis groups, with frequent collaboration through the University of Debrecen's linguistics research clusters.

Márta Seebauerمشاهده پروفایل

دانشیار

• Artificial Intelligence
• Computer Science
• Civil Engineering
• +۵ مورد دیگر

Dr. Márta Seebauer is an Associate Professor at Alba Regia Faculty of Óbuda University. Her research spans interdisciplinary areas including artificial intelligence applications in energy systems, structural engineering reliability analysis, financial risk modeling, and sensor technology for food quality assessment. She maintains an active publication record with work showcased in IEEE symposiums and specialized journals. Email: seebauer.marta@uni-obuda.hu Consultation Hours: Thursdays 14:00-15:00 Her research interests emphasize practical applications of computational methods in civil, environmental, and smart city technologies. Recent work includes neural network-based energy monitoring systems and asbestos risk mitigation strategies during building demolition.

Gyula Simonمشاهده پروفایل

استاد

• Sensor Networks
• Localization Systems
• Signal Processing
• +۳ مورد دیگر

Prof. Gyula Simon is a faculty member at Óbuda University's Alba Regia Faculty, where he holds the rank of Professor. His research focuses on sensor networks, localization systems, and signal processing. He has contributed extensively to advancements in technologies like TDOA-based positioning, VLC communication, and acoustic source tracking. With over two decades of academic work, his publications span applications ranging from agricultural sensors to fault-tolerant indoor positioning systems. Key research interests include developing robust localization algorithms for both outdoor and indoor environments, optimizing wireless sensor networks for energy efficiency and reliability, and integrating emerging technologies like visible light communication (VLC) for beaconing and tracking. His work bridges theoretical signal processing with practical implementations in fields like smart agriculture and security systems. Recent articles highlight innovation in hyperbolic localization methods, sparse sampling techniques for camera systems, and semi-automatic plant growth monitoring. Despite prolific publication output, no scientific awards are explicitly listed. Consultation hours are arranged via email at simon.gyula@amk.uni-obuda.hu, with his office located at Building F Room 316 in Székesfehérvár.

Charaf Hassanمشاهده پروفایل

استاد

• Distributed Systems
• Network Coding
• Internet of Things (IoT)
• +۱۲ مورد دیگر

Charaf Hassan is a Professor and Head of Department at the Budapest University of Technology and Economics, specifically in the Department of Automation and Applied Informatics. His work spans interdisciplinary domains, focusing on distributed systems, network coding, and IoT technologies. His research interests include Distributed Systems and Domain-Specific Modeling Network Coding and Mobile Peer-to-Peer Systems Model-Driven Development for Multiplatform Applications Machine Learning in Fluid Dynamics and Pharmaceutical Analysis Recent publications highlight trends in applying convolutional neural networks to viscosity estimation, model-driven methodologies for IoT, and network coding in cloud storage. He teaches advanced courses in distributed systems and software architectures at the university level.

Dunaev Dmitriyمشاهده پروفایل

دانشیار

• Hardware Security
• Physical Unclonable Functions (PUFs)
• Software Obfuscation
• +۳ مورد دیگر

Dmitriy Dunaev 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 hardware security, particularly through Physical Unclonable Functions (PUFs), software obfuscation, and FPGA-based security solutions. Current position: Associate Professor Institution: Budapest University of Technology and Economics Department: Automation and Applied Informatics Research spans cryptographic security enhancement via configurable hardware designs, machine learning vulnerability analysis, and optimization of security protocols in embedded systems. Recent publications investigate temperature sensitivity, bit configuration in PUFs, and FPGA implementation challenges. Contact: dunaev@aut.bme.hu

Balázs Rakosمشاهده پروفایل

دانشیار

• Nanotechnology
• Biophysics
• Optical Computing
• +۵ مورد دیگر

Dr. Balázs Rakos is an Associate Professor at the Budapest University of Technology and Economics (BME), affiliated with the Department of Automation and Applied Informatics . His research bridges nanotechnology, biophysics, and optical computing. His work focuses on: Integrating photoswitchable proteins with photonic devices for optical computing Developing infrared energy harvesting systems using nanoantennas and MIM diodes Modeling dipole-dipole and Coulomb-coupled protein arrays for molecular electronics Designing self-adapting pixel antenna systems for dynamic signal processing His publications from 2025–2015 reveal a trajectory from infrared sensor technologies to biophotonics and renewable energy applications , with a recurring emphasis on nanoscale biomolecular systems .

Stumpf Péterمشاهده پروفایل

دانشیار

• Electrical Engineering
• Control Systems
• Power Electronics
• +۳ مورد دیگر

Péter Stumpf is an Associate Professor at the Budapest University of Technology and Economics (BME), affiliated with the Department of Automation and Applied Informatics. His research focuses on advanced control systems, power electronics, and machine learning applications in electrical drives. Contact Information: • Office: Building Q.B114, 1117 Budapest, Magyar tudósok krt. 2. Hungary • Phone: +36 (1) 463-2870 • Email: Stumpf.Peter@aut.bme.hu His recent work explores predictive control methods, including Model Predictive Control (MPC) and Reinforcement Learning (RL), applied to permanent magnet synchronous motors, grid-side converters, and high-speed drives. He has developed novel algorithms for optimal current computation, weighting factor assignment, and harmonics compensation. Key research trends include: Integration of machine learning in control systems Optimization of power electronics for renewable energy Advanced modulation techniques in motor drives Compensation of nonlinear effects in high-speed systems

Husam Al-Magsoosiمشاهده پروفایل

عضو هیئت علمی

• Hardware Security
• Physical Unclonable Functions (PUFs)
• Machine Learning in Security
• +۴ مورد دیگر

Husam Al-Magsoosi is an Assistant Research Fellow at the Budapest University of Technology and Economics , affiliated with the College of Engineering and the Department of Automation and Applied Informatics . His work focuses on hardware security, particularly in the development and analysis of Physical Unclonable Functions (PUFs) . Research Interests : Hardware Security, PUFs, FPGA Design, Machine Learning in Security, Embedded Systems, Wireless Sensor Networks. His recent publications highlight advancements in configurable ring oscillator PUFs, addressing security, performance optimization, and environmental factors like temperature sensitivity. He explores FPGA-based implementations and evaluates vulnerabilities to machine learning attacks. His work also extends to energy-efficient routing protocols for sensor networks and embedded system design. Scientific Awards : No specific awards mentioned in the provided data.

Krisztián Pomáziمشاهده پروفایل

مدرس

• Educational Technology
• Bioinformatics
• Cognitive Science
• +۳ مورد دیگر

Krisztián Pomázi is a Lecturer at the Budapest University of Technology and Economics , affiliated with the Faculty of Electrical Engineering and Informatics and the Department of Automation and Applied Informatics . His work bridges educational technology and cognitive science , utilizing machine learning and bioinformatics to enhance learning experiences. Department: Automation and Applied Informatics Email: Pomazi.Krisztian@aut.bme.hu Research interests include: Adaptive learning systems integrating biofeedback Machine learning applications in cognitive workload assessment Psychological profiling using computational models Usability evaluation via biomedical signal processing Intelligent exercise generation for cognitive assessment Educational game mechanics with physiological feedback Recent publication trends show a focus on blending machine learning with human-computer interaction to create personalized educational tools. His work incorporates cognitive science principles to dynamically adjust learning environments using biofeedback data, while also exploring psychometric and usability dimensions in digital education. Contact: Pomazi.Krisztian@aut.bme.hu

• Transportation
• Sustainable Transport
• CO2 Emissions
• +۴ مورد دیگر

Dr. Ádám Török is a prominent researcher affiliated with the Budapest University of Technology and Economics (BME) and the Institute of Transport Sciences (KTI) . Active since 2000, he specializes in transport economics, emissions modeling, and sustainable mobility systems. His work spans 2024-2026 and focuses on autonomous vehicles, CO2 decomposition techniques, and public transportation sustainability. 2000-2012: Department of Transport Economics at BME 2013-2020: Department of Transport Operations and Transport Economics at BME 2021-present: Department of Transport Technology and Transport Economics at BME 2018-present: Institute of Transport Sciences (KTI) His research integrates environmental impact analysis with transport policy modeling , emphasizing autonomous vehicle economics and CO2 emission drivers . Recent publications in Transport Policy , Energy Reports , and Journal of Economy and Technology demonstrate expertise in scenario-based forecasting and multi-criteria sustainability assessment . Key article trends show collaboration with international researchers like Ammar Al-lami and Anas Alatawneh, combining machine learning with transport economics to address challenges in European mobility systems . His work appears in journals categorized as Q1-Q2 by SJR indicators across transportation, environmental science, and engineering disciplines. Dr. Török contributes to academic committees including: Doctoral Qualification Committee in Economics (IXGJO GMB) International Committee on Political Science and Law (IXGJO ÁJB) Sociological Scientific Committee (IXGJO SZTB) He advises doctoral students and publishes extensively on automated vehicle adoption , transport safety , and alternative drive chains . Current projects suggest ongoing engagement with European transport policy and climate resilience initiatives.

Attila Imreمشاهده پروفایل

استاد

• thermodynamics
• energetics
• physical chemistry
• +۹ مورد دیگر

Dr. Attila Imre is a Full-Time Professor in the Department of Power Machines and Systems at Budapest University of Technology and Economics (BME) . He also serves as a Part-Time Scientific Advisor at the MTA Energy Research Center . His research spans thermodynamics, energetics, physical chemistry, and ecology, with a focus on working fluids, phase transitions, and energy systems. Doctor of Science (DSc), Hungarian Academy of Sciences (2015) PhD in Physics, ELTE (1996) DrUniv in Solid-State Physics, ELTE (1994) MSc in Physics, ELTE Faculty of Physics (1990) Imre’s research integrates theoretical and applied studies in thermodynamic cycles, metastable fluids, and supercritical systems. He has pioneered work on working fluid selection, cycle efficiency, and cold energy utilization, particularly in organic Rankine cycles and power-to-methane technologies. His 15 most recent publications emphasize artificial intelligence in energy systems, economic analyses of sustainability, and thermodynamic modeling of extreme-state fluids. Key trends include AI-driven performance mapping, techno-economic evaluations of waste heat recovery, and ecological applications of fractal geometry. Scientific Awards : Humboldt Scholarship, Johannes Gutenberg University, Mainz, Germany (1999) Imre has held prestigious postdoctoral roles at the University of Tennessee and senior research positions in Hungarian institutions. His work bridges energy engineering, computational modeling, and interdisciplinary challenges in translation and cultural studies.

Eszter Rita Katonaمشاهده پروفایل

استادیار

• Computational Social Science
• Social Research Methodology
• Natural Language Processing
• +۷ مورد دیگر

Eszter Rita Katona is an Assistant Professor at Eötvös Loránd University's Faculty of Social Sciences, Department of Social Research Methodology. She serves as a lecturer at multiple research centers including the Research Center for Computational Social Science (RC2S2), Survey Methods Room Budapest, and Széchenyi István College for Advanced Studies. Education: PhD in Interdisciplinary Social Research (Doctoral School of Sociology, 2018-2023) Computer Science specialization (Faculty of Informatics, 2016-2017) Survey Statistics MSc (Faculty of Social Sciences, 2015-2018) Social Sciences BA (Faculty of Social Sciences, 2011-2015) German Studies BA (Faculty of Humanities, 2012-2015) Angelusz Róbert College for Advanced Studies (2014-2018) Research Focus: As a computational social scientist, her work spans three major domains: NLP and data visualization applications in social research Discursive framing of depression in online communities Corruption risk assessment in public procurement Teaching Expertise: In her academic role, she teaches: BA courses: Data Collection Methods, Data Visualization, Introduction to Sociological Research, Quantitative Data Analysis MSc courses: Advanced Data Visualization, Python Programming, Communication and Data Visualization, Text Analytics Scientific Contributions: Her recent publications and conference presentations focus on: Machine learning for depression discourse analysis Digital lens approach to Holocaust testimonies Corruption risk modeling in public procurement Interdisciplinary NLP applications Computational social science methodology Contact: katona.eszter@tatk.elte.hu

Márton Karsaiمشاهده پروفایل

دانشیار

• Network Science
• Computational Social Science
• Data Science
• +۵ مورد دیگر

Márton Karsai is an Associate Professor and Head of the Department of Network and Data Science at Central European University (CEU). He also serves as a Research Professor at the Rényi Institute of Mathematics (Hungary) and Editor-in-Chief of Advances in Complex Systems . His work focuses on computational social science, human dynamics, and data-driven modeling of socioeconomic systems. Karsai holds advanced degrees including a DSc from the Hungarian Academy of Sciences and an HDR (Habilitation) in Computer Science from École Normale Supérieure de Lyon. His research integrates temporal networks, human mobility, and social contagion phenomena, often using large-scale datasets from digital platforms and wearable sensors. Notable projects include studies on evacuation behavior during disasters, vaccination hesitancy, and urban socioeconomic stratification. Karsai leads interdisciplinary initiatives like the DyLNet project, which examines social interactions and language development in preschool environments through sensor technology. Recent publications highlight innovations in network clustering algorithms (PASCO), epidemic modeling with generalized contact matrices, and the application of machine learning to infer socioeconomic status from satellite imagery. His work bridges computational methods with real-world challenges in public health, urban planning, and humanitarian development.

• Critical Care Medicine
• Respiratory Medicine
• Neuromuscular Disorders
• +۳ مورد دیگر

Nicolas Terzi is a researcher in the field of critical care medicine, specializing in respiratory failure, neuromuscular disorders, and mechanical ventilation. He is affiliated with the University of Caen and has served as a thesis director for medical and doctoral theses. His research focuses on innovative ventilation modes such as NAVA (Neurally Adjusted Ventilatory Assist), ARDS management, and the interplay between respiratory and deglutition functions in neuromuscular diseases. Terzi has contributed to numerous studies on critical care interventions, including proning strategies, plasma exchange outcomes, and ICU staffing guidelines. His work frequently addresses challenges in respiratory support, particularly in pandemic contexts like severe ARDS related to COVID-19. He collaborates with interdisciplinary teams across Europe and has published extensively on ventilator protocols, imaging in critical care, and patient outcomes.