جستجوی استاد راهنمای دانشگاهی

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

Kinga Tünde Kruppaمشاهده پروفایل

استادیار

• Geometric Modeling
• Computer Aided Geometric Design
• Computer Graphics

Dr. Kinga Tünde Kruppa serves as an Assistant Professor in the Department of Data Science and Visualization at the Faculty of Informatics, University of Debrecen, where she specializes in geometric modeling and computer-aided design. Her academic role integrates theoretical and applied research within the department's broader focus on computational geometry and visualization. Her core research interests include: Geometric Modeling Computer Aided Geometric Design Computer Graphics Dr. Kruppa maintains consistent student engagement through scheduled office hours on Mondays (10:00-11:00) and Tuesdays (15:00-16:00), with primary communication via institutional email. Her work contributes to the department's research ecosystem in data science and visualization, though specific collaborative projects or grants are not detailed in available records.

• Computer modeling of curves and surfaces
• Constructive and representational geometry
• 3D technologies
• +۳ مورد دیگر

Ildikó Papp is an Associate Professor at the Faculty of Informatics, University of Debrecen , specializing in the Department of Data Science and Visualization . Her academic focus spans geometric modeling , 3D technologies , and experience-oriented teaching methods , bridging theoretical geometry with practical digital applications. Research Interests: Computer modeling of curves and surfaces Constructive and representational geometry 3D printing and visualization Cognitive infocommunication in education Publication Trends: Focus on QR code integration with 3D surfaces (2021-2022) Biomedical applications of FDM printing (2020) Educational impact of 3D technologies (2016-2018) Advancements in Bézier curve isoptics (2012-2013) Optimization techniques in geometric modeling (2012) Contact: Email: papp.ildiko@inf.unideb.hu

• High-Performance Data Transfer
• Parallel Data Processing
• Memory-Safe Programming (Rust)
• +۳ مورد دیگر

Róbert Tornai serves as an Associate Professor in the Department of Data Science and Visualization at the Faculty of Informatics, University of Debrecen, Hungary. His institutional affiliation encompasses active participation in the department's core mission of advancing data processing, visualization, and computational methodologies within Hungary's academic landscape. His primary research focuses on high-performance data transfer in supercomputing environments, parallel data processing using memory-safe Rust programming, and virtual collaboration system development. These interconnected domains emphasize optimizing data-intensive workflows while ensuring system security and user accessibility, reflecting contemporary challenges in distributed computing infrastructure. Analysis of his 15 most recent publications reveals dominant trends in high-speed connectionless networking protocols (2020-2025), where he investigates performance optimization, error detection, and encryption for file transfer systems. Significant secondary themes include biometric security applications (iris/voice recognition) and GPU-accelerated image processing techniques leveraging WebAssembly and Vulkan API, demonstrating technical versatility across networking, security, and visualization domains. His scholarly output consistently addresses practical implementation challenges in data transfer and secure systems, with recent work extending into educational technology applications of 3D printing. This trajectory indicates sustained engagement with evolving computational paradigms while maintaining focus on real-world system performance and security requirements.

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

• Statistical Literacy
• Financial Literacy
• Statistics Education
• +۵ مورد دیگر

Dr. Péter Kovács is an Associate Professor and Chair of the Department of Statistics and Demography at the University of Szeged, serving as Dean of the Faculty of Economics and Business Administration since 2017. Previously, he was Vice Dean (2014–2017). He holds a PhD and habilitation in Economics and an MA in Mathematics. His research focuses on statistical and financial literacy, multivariate statistical methods, and education technology. He leads the Financial Literacy Research Group and participates in initiatives like ProCivicStat. He has extensive editorial roles, including membership in the editorial boards of Pakistan Journal of Statistics and Operation Research , Journal of Applied Economics and Business , and others. He chairs the Hungarian Academy of Science's Statistics Scientific Subcommittee and holds leadership roles in international organizations like the International Association for Statistical Education (IASE) and the International Statistical Literacy Project (ISLP). His research interests bridge statistical methodology with societal issues, including the acceptance of autonomous vehicles, maternal mortality in sub-Saharan Africa, and the integration of visualization tools in education. He has been awarded the Péter György Award (2006) for teaching and recognized as Ambassador of Financial Literacy (2021). Teaching responsibilities include courses on statistics, econometrics, and business software. He emphasizes modern pedagogy, including technology-driven methods and collaborative learning approaches. His work addresses both theoretical advancements and practical applications in education and policy.

• Market Research
• Marketing Research
• Consumption Sociology
• +۴ مورد دیگر

Andrea Gregory is an Assistant Professor in the Sociology Department at Károli Gáspár Reformed University's Faculty of Humanities and Social Sciences, where she is affiliated with the Institute of Social and Communication Sciences. Born in Budapest in 1969, she has established herself as a researcher focusing on civil society, reciprocity, and market research methodologies within the Hungarian academic landscape. Education: MA in Sociology from ELTE (Eötvös Loránd University), 1997 Program certificate in Cultural Management Training Program from ELTE, 1997 Dr. Gregory's research primarily centers on civil society organizations, reciprocity mechanisms, and market research methodologies. Her work demonstrates a consistent focus on understanding social interactions within civil organizations, particularly examining how reciprocity functions in various contexts including during crises like pandemics. She has increasingly focused on the relationship between digital technologies and traditional social structures. Analysis of her publication history reveals a clear trajectory from traditional market research topics toward more specialized sociological investigations of civil society. Her most recent work (2020-2024) consistently examines reciprocity within civil organizations, pandemic impacts on social structures, and the influence of digital technologies on traditional social networks. This represents a significant specialization within sociological research on civil society dynamics. Professional Affiliations: Member of MSZT (Hungarian Sociological Society) Dr. Gregory has held various research and teaching positions throughout her career. Before joining Károli Gáspár Reformed University, she served as an Assistant Professor at BGF Faculty of Foreign Trade, Research Director at Capital Research, and Senior Researcher at Hoffmann Research International. Her professional background combines academic teaching with practical market research experience, which informs her interdisciplinary approach to sociological research. Her work environment at the Institute of Social and Communication Sciences provides a suitable context for her research on civil society organizations and communication dynamics within social structures. The department's focus on social sciences creates an appropriate academic home for her specialized research interests in reciprocity and civil society organization dynamics.

Asztalos Márkمشاهده پروفایل

دانشیار

• Model-Driven Engineering
• Software Engineering
• Graph Rewriting Systems
• +۳ مورد دیگر

Márk Asztalos is an Associate Professor 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 . He leads research in the Visual Modeling Group, focusing on model-driven engineering, graph rewriting systems, and domain-specific languages. Research Interests: Model transformation verification, text-based modeling, graph pattern matching, and cloud/mobile system modeling. Contact: E-mail: Asztalos.Mark@aut.bme.hu , Office: Q.B226, Department of Automation and Applied Informatics, BME. His publications emphasize model transformation verification (2010-2015), graph rewriting techniques for pattern matching (2015-2017), and domain-specific language design (2014). Recent work (2020) analyzes model integration challenges in model-driven methodologies. Contact details: Address: Budapest 1117, Magyar tudósok krt. 2, Hungary Phone: +36 (1) 463-3702

• Geospatial Information
• Remote Sensing
• GIS
• +۴ مورد دیگر

Attila Juhász serves as an Associate Professor within the Department of Photogrammetry and Geoinformatics at the Faculty of Civil Engineering, Budapest University of Technology and Economics (BME). His academic responsibilities include teaching courses such as Digital Surface Modeling, Geospatial Information, Civil Engineering Informatics, and Monitoring and GIS, alongside supervising thesis work through course BMEEOFTTATZ. He maintains active research in geospatial technologies with emphasis on historical applications. His research program centers on applying geospatial information systems and remote sensing to reconstruct historical military operations, particularly World War II events. He develops methodologies for bomb crater detection, fortification mapping, and battlefield analysis using LiDAR and multi-temporal GIS. A significant contribution involves solving temporal data management challenges in historical reconstructions, enabling accurate modeling of evolving military landscapes. His work bridges technical geospatial innovation with humanities scholarship in archaeology and military history. Analysis of his publication record reveals consistent specialization in automated detection of World War II artifacts through LiDAR and spatial data fusion. His research demonstrates progressive technical sophistication from early 2000s case studies to current AI-enhanced object recognition systems. The work establishes critical frameworks for conflict archaeology and has produced notable reconstructions including Budapest defense lines and the Attila-line fortifications. No scientific awards or major fellowships are documented in the available sources. Dr. Juhász supervises thesis research as evidenced by course BMEEOFTTATZ, but specific student names and research grant details remain unreported in the source material. His teaching portfolio indicates extensive mentorship across undergraduate and graduate geospatial curricula. He maintains operational affiliation with the Endre Németh Measurement Station and Education Center, which provides critical infrastructure for geospatial data collection, LiDAR processing, and field-based historical reconstruction projects. This facility supports both his research initiatives and practical student training in advanced surveying techniques.

Marcell Beregi-Kovácsمشاهده پروفایل

مدرس

• Machine learning
• Deep learning
• Optimization
• +۳ مورد دیگر

Marcell Beregi-Kovács is a Lecturer at the Department of Data Science and Visualization within the Faculty of Informatics at the University of Debrecen. His work focuses on machine learning, deep learning, optimization, and anomaly detection , aligning with the department's broader research in data science and visualization. The Department of Data Science and Visualization conducts research in areas including data processing, geospatial information systems, and computer graphics. Marcell contributes to educational and research activities within these domains. For direct inquiries, Marcell can be contacted at beregi.kovacs.marcell@inf.unideb.hu . His office is located in room I120 of the Faculty of Informatics building at 4028 Debrecen, Kassai Street 26.

Dániel Bence Erősمشاهده پروفایل

مدرس

• Data Science
• Data Visualization
• Machine Learning
• +۵ مورد دیگر

Dániel Bence Erős serves as a teaching assistant at the University of Debrecen's Faculty of Informatics within the Department of Data Science and Visualization. His institutional affiliation places him within Hungary's prominent academic hub for computational sciences, working from office I122 in the Faculty of Informatics building at Kassai Street 26, Debrecen. The Department of Data Science and Visualization conducts research and education across critical computational domains including data processing pipelines , advanced visualization techniques , neural network architectures , and geometric modeling systems . Their work spans both theoretical frameworks and practical implementations in machine learning, image analysis, and spatial data systems. As part of this department, Erős contributes to academic instruction within Hungary's growing AI and data science education ecosystem. The department maintains active research in medical imaging, cryptographic systems, and computational geometry through its diverse faculty team. His professional activities operate within the institutional framework of the University of Debrecen, a major Central European research university with strong computational science programs. The department maintains collaborative relationships across multiple technical domains including medical informatics, blockchain systems, and 3D visualization technologies.

Henrietta Tománمشاهده پروفایل

استادیار

• Medical image processing
• Fusion systems
• Quasigroups
• +۳ مورد دیگر

Dr. Henrietta Tomán serves as an Assistant Professor in the Department of Data Science and Visualization at the University of Debrecen's Faculty of Informatics, where she bridges advanced mathematical theory with practical medical imaging applications. Her work integrates abstract algebraic structures with cutting-edge AI systems to solve critical healthcare challenges. Her research portfolio spans three interconnected domains: Medical image processing (particularly ensemble-based segmentation and quality assessment for ophthalmic diagnostics) Geometric structures (quasigroups, loops, and differentiable manifolds) Stochastic optimization for resource-constrained AI systems Analysis of her publication trajectory reveals evolving expertise: early work (2010-2014) established foundations in geometric loop theory applied to image processing, while recent research (2020-2024) pioneers stochastic fusion techniques for medical image ensembles under computational constraints. Her most significant contributions involve translating mathematical abstractions into robust clinical decision-support tools, particularly in diabetic retinopathy detection and epidemic modeling. Current work demonstrates increasing focus on real-time AI systems that maintain accuracy under hardware limitations, reflecting urgent needs in telemedicine and mobile health applications. Dr. Tomán maintains active collaboration within the Doctoral School of Informatics and contributes to Hungary's national research initiatives in medical AI, with consistent publication output in top-tier venues spanning computer vision, medical imaging, and mathematical computing.

Jozsef Fiserمشاهده پروفایل

استاد

• Cognitive Science
• Visual Statistical Learning
• Perceptual Decision-Making
• +۵ مورد دیگر

Jozsef Fiser is a Professor in the Department of Cognitive Science at Central European University (CEU), where he serves as Director of the Center for Cognitive Computation. His research bridges human psychophysical experiments, computational modeling, and neurophysiological studies to explore how visual statistical learning shapes internal representations for cognition and behavior. He holds advanced degrees in Psychology (D.Sc., Hungarian Academy of Sciences; Dr. habil., Janus Pannonius University), Computer Science (Ph.D., University of Southern California), and Electrical Engineering (Diploma, Technical University of Budapest). D.Sc. in Psychology, Hungarian Academy of Sciences (2007) Dr. habil. in Psychology, Janus Pannonius University (2004) Ph.D. in Computer Science, University of Southern California (1997) M.A. in Psychology, University of Southern California (1992) Diploma in Electrical Engineering, Technical University of Budapest (1986) His research focuses on hierarchical object representations, active learning, probabilistic computation in the brain, and the link between beliefs and knowledge. Key themes include temporal processing, cross-modal integration, attention, and neural variability during perceptual learning. His work often examines how low-level visual processes (e.g., orientation coding) relate to higher-level cognitive functions. Analysis of his recent publications reveals trends in visual statistical learning , probabilistic inference , and neural sampling as frameworks for understanding cognition. Many studies investigate how uncertainty, memory consolidation, and attention modulate learning across species (humans, honeybees, chicks) and contexts (naturalistic vision, sleep effects). As Director of CEU's Center for Cognitive Computation, Fiser leads interdisciplinary research linking computational models with empirical studies of perception, decision-making, and neural dynamics.

• Sociolinguistics
• Bilingualism and Multilingualism
• Hungarian as a Foreign Language
• +۴ مورد دیگر

Dr. Ildiko Schmidt is an Associate Professor at the Károli Gáspár Reformed University , affiliated with the Faculty of Humanities and Social Sciences and the Department of Hungarian Linguistics . Her career spans over two decades, combining academic research with practical applications in language teaching. Education : PhD in Linguistics (2018), University of Pécs MA in Linguistics (2008), University of Pécs Qualifications in Hungarian as a Foreign Language Teaching (2008), Hungarian Language and Literature (2006), and Primary School Teaching (1996) Schmidt’s research focuses on Sociolinguistics (bilingualism, multilingualism) and Teaching Hungarian as a Foreign Language . Her work explores linguistic integration of migrant children, literacy development, and educational methodologies for diverse classrooms. Her publications (15 most recent) emphasize language policy, cross-cultural communication, and practical pedagogical models like the Dual Model. She supervises doctoral students in areas such as Technical Language Communication and Methodological Issues in Hungarian Language Instruction , and has opposed dissertations on bilingualism in Chinese and Roma communities. Schmidt is a Charter Member of KorSzak and Member of MANYE, with C1 proficiency in English and German, and B2 in French.

• Administrative Law
• Infocommunication and Law
• Information Society
• +۹ مورد دیگر

Zsolt Czékmann is an Assistant Professor at the Faculty of Political Science and Law, University of Miskolc, where he serves as Head of the Department of Administrative Law. His academic career spans roles including researcher in projects like EFOP-3.6.2-16-2017-00007 and former Director of the University of Miskolc Regional Center for Adult Education. PhD in Legal Studies (University of Pécs) Doctoral degree in Law and Public Administration (University of Miskolc) His research focuses on administrative law, e-government, information society, and blockchain applications in public administration. He has explored topics such as automated decision-making, telemedicine regulation, and cross-border contract practices. His recent work emphasizes digital transformation in governance and environmental law. Key award highlights include the University of Miskolc Meritorious Lecturer Award (2017) and the OTDK Consultant Special Award (2015). He contributes to journals like Infocommunication and Law and serves on boards for educational development projects. Czékmann's international collaboration includes comparative analysis of EU administrative systems.