Find Academic Supervisors

• Autonomous Driving
• Edge Computing
• Blockchain Technology
• +7 more

Šlapak Eugen is an Assistant Professor at the Technical University of Košice. His research focuses on autonomous driving systems, edge computing, and network optimization, with a particular emphasis on applying neural networks and blockchain technologies in vehicular and 5G networks. Eugen Šlapak holds a PhD in [specific field not explicitly stated, likely Engineering/Computer Science] and an Ing. (engineer) degree. His academic background combines technical expertise in telecommunications and computer science. His research interests span autonomous driving technologies, including simulation and control systems, as well as edge computing and metaverse integration. He also explores blockchain applications in vehicular networks, resource allocation in 5G and beyond, and the use of graph neural networks for network optimization. His work intersects machine learning, robotics, and telecommunications to address challenges in modern communication systems and intelligent transportation. Recent publications highlight advancements in neural radiance fields for industrial robotics, distributed edge video compression for autonomous driving, and blockchain-based resource allocation in connected vehicles. Earlier work includes optimization of UAV-assisted networks and HetNet topology design using machine learning clustering methods. While no formal awards are listed, his contributions to vehicular networks, edge computing, and AI-driven network design reflect significant scholarly impact. Advising details are not documented here, but his research collaborations likely involve cross-disciplinary teams focusing on autonomous systems and 5G infrastructure. No lab affiliations or teams are explicitly mentioned, though his teaching role in the course Stochastické modelovanie a analýza dát (SMaAD) suggests involvement in data analysis and stochastic modeling initiatives.

• Neural Networks
• Deep Learning
• Biomedical Signal Analysis
• +4 more

Máté Hireš is an Assistant Professor at the Technical University of Košice's Department of Computers and Informatics. He earned his PhD in computer science from the same institution, specializing in Parkinson's disease diagnosis using deep learning for voice analysis. His doctoral research extended his master's thesis on distributed neural radiance fields for autonomous vehicles. Hireš's work bridges neural networks, deep learning, and biomedical applications, particularly in analyzing handwriting, speech, and signal data for neurological disorder detection. His publications demonstrate consistent focus on Parkinson's disease diagnostics through innovative machine learning approaches applied to voice recordings and handwriting samples. Research Focus Deep learning for pathological speech detection Handwriting analysis for neurodegenerative diseases Robust diagnostic model development Biomedical signal processing

• Sustainable development in business
• Design thinking in higher education
• Corporate foresight
• +3 more

Brigita Boorová serves as an Assistant Professor at the Department of Business Economy , Faculty of Business Management , University of Economics in Bratislava . She has held this position since 2013 and previously worked as an Assistant Professor (2002–2010) at the same faculty. Key skills: Pedagogical innovation, digital education (Microsoft Digital University), design thinking, and interdisciplinary research Projects: Erasmus+ DT.Uni, Visegrad Fund FOR_V4, KEGA 022EU-4/2021, VEGA 1/0465/23 International Experience: Bifröst University (Iceland), University of Economics in Katowice (Poland), TU Dresden (Germany), and institutions in Poland, Czech Republic, and Italy Her research focuses on sustainable development , logistics , and corporate foresight . She has published in journals like European Journal of Futures Research and Economics of Enterprise , with 5 citations in WoS/Scopus. Her work often addresses interdisciplinary education , design thinking , and environmental production optimization . She has supervised 33 bachelor's and 42 master's theses and participated in reviewing academic competitions. Her projects emphasize sustainability, innovation, and modern didactic methodologies in higher education.

• Game Theory
• Econometrics
• Quantitative Methods in Economics
• +3 more

Allan Jose Sequeira Lopez is an Assistant Professor at the Department of Romance and Slavic Languages within the Faculty of Applied Languages at the University of Economics in Bratislava. His academic career spans teaching, research, and international collaboration. PhD in Economics and Management (2021) MSc in Quantitative Methods in Economics (2015) Research Interests : Lopez specializes in Game Theory , applying multi-criteria decision-making models to Spatial Competition and economic policy. His work explores regulatory interventions, bimatrix games, and evolutionary algorithms in economic contexts. Scientific Contributions : His research includes 2 WoS/Scopus-registered outputs and participation in VEGA projects like 1/0351/17 and 1/0427/20 , focusing on game-theoretic applications for economic problems in Slovakia. International Engagement : He has conducted lectures and research at institutions including Masaryk University (Brno), University of Las Palmas de Gran Canaria, and Jihlava Polytechnic University, emphasizing cross-border academic exchange.

Peter SzabóView profile

Associate Professor

• Mathematics
• Linear Algebra
• Computer Algebra
• +5 more

Peter Szabó is an Associate Professor at the Department of Aviation Technical Training , Faculty of Aeronautics , Technical University of Košice , Slovakia. He is actively involved in research at the intersection of mathematics, computer algebra, and aerospace engineering. Academic Affiliation: Technical University of Košice, Faculty of Aeronautics, Department of Aviation Technical Training Research Interests include: Mathematical modeling in aviation (Free Route Airspace, complex networks) Linear algebra and numerical methods with MATLAB/SageMath Calculus education and computational techniques Graph theory applications to air traffic systems Recent Article Trends highlight: Integration of calculus and numerical analysis for educational tools (2025) Mathematical axioms for airspace modeling (2022) Cloud computing in aviation research (2022) Linear algebra textbooks and computational exercises (2019) Advising : Mentored students on topics ranging from satellite stabilization to air traffic optimization.

• Fuzzy Sets
• Intuitionistic Fuzzy Sets
• Data Analysis
• +6 more

Alžbeta Michalíková serves as Associate Professor at Matej Bel University's Faculty of Arts, Department of Computer Science. Her academic profile spans mathematical foundations and applied computational research with significant contributions to fuzzy logic systems. Her research focuses on Fuzzy Sets and Intuitionistic Fuzzy Sets with applications in Computer Vision, Biology, and Medicine. She investigates mathematical properties of these structures and explores integrations with Neural Networks and Evolutionary Algorithms. Recent work emphasizes smart city applications, air quality analysis, and digital education tools. Her publication trends show evolution from theoretical fuzzy mathematics (2005-2015) to applied AI systems (2020-present), particularly in environmental monitoring and transportation systems. Key themes include uncertainty modeling, image classification, and real-time data processing for urban applications. Erasmus+ KA2 projects on air pollution technologies (2022-2024) KEGA projects for digital educational tools (2020-2025) VEGA research on fuzzy models (2011-2017) APVV projects on scientific outreach She teaches Mathematics for Computer Scientists, Numerical Methods, and specialized Fuzzy Sets courses. Her technical infrastructure includes ORCID (0000-0002-0568-9279), SCOPUS (24448471500), and ResearchGate profiles. Current work focuses on digital identification keys for mycology education and AI-driven smart city analytics.

Ladislav VéghView profile

Associate Professor

• Computer Science Education
• Educational Technology
• Artificial Intelligence
• +5 more

Ladislav Végh, PhD., serves as an Associate Professor in the Department of Informatics at the Faculty of Economics and Informatics, J. Selye University in Komárno, Slovakia. With an office in TP3C and contactable via veghl@ujs.sk, he has maintained continuous academic employment at the university since 2005. His academic journey includes university studies in teaching mathematics-informatics at Constantine the Philosopher University in Nitra (1994-1999), examina rigorosa in teaching informatics at J. Selye University (2007-2008), and PhD studies in Basics and Methodology of Informatics at ELTE, Budapest (2009-2018). Végh's research focuses on innovative approaches to computer science education, particularly teaching programming through interactive methods. His primary research interests include teaching programming using animations, machine learning applications in education, and artificial intelligence integration in pedagogical contexts. He has consistently explored how game-based learning and visual representations can enhance students' understanding of complex programming concepts, with particular emphasis on algorithmic thinking and object-oriented programming principles. His publication record demonstrates a clear trajectory from foundational work on algorithm animations for teaching sorting concepts toward increasingly sophisticated applications of machine learning and deep learning in educational contexts. Recent publications show expansion into medical informatics applications, cultural heritage preservation through 3D modeling, and pandemic-era educational adaptations, while maintaining his core focus on programming education methodologies. His work frequently appears in reputable international conferences and journals, with growing citation impact. Electronic support of teaching programming (2008-2010) Terminology in e-learning (2009-2011) Modeling and animation-simulation models in e-learning (2011-2013) Modelling, simulation and animation in education (2014-2016) Interactive animation and simulation models in education (2018-2020) Analysis of natural and mathematical education at high schools (2019-2021) Interactive animation and simulation models for deep learning (2021-2023) Intelligent Animation-Simulation Models for Deep Learning (2024-2026) Végh has secured significant research funding through multiple KEGA and VEGA projects, demonstrating sustained research productivity and relevance. His work bridges theoretical computer science concepts with practical educational applications, particularly focusing on how interactive visualizations and game mechanics can transform programming education. His current projects indicate continued exploration of deep learning applications in educational contexts, suggesting an evolving research agenda that maintains educational technology at its core while expanding into more advanced AI methodologies.

Zuzana ČičkováView profile

Associate Professor

• Operations Research
• Game Theory
• Econometrics
• +2 more

Zuzana Čičková is an Associate Professor at the Department of Operations Research and Econometrics, Faculty of Economic Informatics, University of Economics in Bratislava. Her work bridges computational intelligence, game theory, and economic modeling, with a focus on spatial competition, logistics, and market dynamics. Academic Rank: Associate Professor Department: Operations Research and Econometrics University: University of Economics in Bratislava Her research spans game theory, vehicle routing, and econometric modeling. Recent projects include multi-criteria game theory applications in spatial allocation (2022), analysis of Arctic shipping routes (2022), and optimization of recycling networks under VEGA grants. She has contributed to algorithm design (SOMA/DE) and market concentration indicators like the Herfindahl-Hirschman Index. Her publications reflect expertise in computational intelligence for economic problems, including vehicle routing with time windows , spatial competition models , and data-driven decision support systems . While no explicit awards are listed, her leadership in VEGA projects (2017-2025) and international collaborations with institutions like Bifröst University and Óbuda University underscores her academic impact. 31 Web of Science/Scopus publications with 98 citations 8 invited lectures at international/national conferences PhD in Econometrics and Operations Research (2005) Teaching since 2001, advising 38 master’s theses She has undertaken international mobilities in Iceland (2014, 2022), Germany (2007), Czech Republic (2022), and Spain (2022), focusing on research and pedagogical innovation. Her current projects include VEGA 1/0115/23 on cooperative game theory in international relations (2023-2025).

Pavel GežíkView profile

Assistant Professor

• Optimization Programming
• Operations Research
• Graph Theory
• +9 more

Ing. Pavel Gežík, PhD., is an Assistant Professor at the Department of Operations Research and Econometrics within the Faculty of Economic Informatics at the University of Economics in Bratislava. Since 2010, he has been actively contributing to academic and research activities in operations research, environmental modeling, and game theory applications. Education: Second degree in Operational Research and Econometrics (2007), Third degree in Econometrics and Operational Research (2010) from University of Economics in Bratislava, Faculty of Economic Informatics His research focuses on optimization programming, game theory models, network analysis, logistics scheduling, and circular economy principles. He has integrated environmental sustainability into reverse logistics frameworks and developed methods for debt modeling in economic systems. Recent publications highlight his work in game theory applications for retail location optimization, circular economy recycling models, and graph theory for economic networks. These studies emphasize mathematical rigor and practical implementation in economic decision-making. He has participated in significant grants such as: VEGA 1/0120/23 - Environmental Models for Eco-Economic Decisions APVV SK-SRB-18-0009 - Logistics Optimization with Electromobility VEGA 1/0320/18 - Green Policy Analysis Over 15 years, he has supervised 25 bachelor's and 22 master's theses, contributing to education in optimization and logistics. His research outputs include 8 Web of Science/Scopus-indexed works with 4 citations.

Jaroslav KULTANView profile

Associate Professor

• Database Systems
• Distance Learning
• Educational Technology
• +3 more

Jaroslav KULTAN serves as an Associate Professor and Deputy Head of the Department of Applied Informatics at the Faculty of Economic Informatics, University of Economics in Bratislava. His office is located in Room E8.27, and his contact email is jaroslav.kultan@euba.sk. Consultation hours are held on Wednesdays (13:00-14:30) and Thursdays (11:00-12:30). He holds a degree from Štátna technická univerzita Ukrajiny (KPI) (1979-1985). Prior to joining academia in 2004, he held positions including Deputy Director at Gymnázium F.G.Lorcu (1996-2004) and roles in technical and energy sectors. KULTAN's research spans two primary domains: Information Technology in Education : Focused on database systems, e-learning methodologies (LMS Moodle), distance learning frameworks, video conferencing applications, adaptive feedback systems, and IT infrastructure for educational quality enhancement. Energy Informatics : Involving energy modeling for buildings, econometric analysis of renewable energy adoption, smart grid technologies, efficiency optimization, and interactive tools for energy education. His publication record (2004-2022) demonstrates consistent focus on: Pedagogical innovations using IT (e-learning frameworks, feedback systems, STEM education tools) Energy systems modeling and sustainable technology integration Cross-disciplinary applications of econometrics and linguistic modeling in operations management Publications frequently appear in international conference proceedings and edited volumes, with collaborations across Slovakia, Russia, and Central Asia. No scientific awards or prizes are documented in the provided text. While no specific students or grants are listed, KULTAN has co-organized international student conferences (e.g., Informačné technológie v ekonomike a vzdelávaní ) and contributed to projects like APVV-0280-10 and VEGA 1/0351/17. His role includes administrative leadership as Deputy Head of Department.

Martin KuchtaView profile

Assistant Professor

• Digital Marketing
• Marketing Management
• Consumer Behavior
• +5 more

Martin Kuchta is an Assistant Professor at the Department of Marketing, Faculty of Economics and Finance, Bratislava University of Economics and Business. His research focuses on digital marketing, consumer behavior, and machine learning applications in marketing. University: Bratislava University of Economics and Business Department: Department of Marketing Research Interests: Digital marketing, influencer marketing, programmatic buying, and data-driven marketing strategies. His work explores the intersection of technology, consumer behavior, and advertising effectiveness. Recent Publications: Analyze shopper marketing dynamics (2022), podcast evolution (2021), ad blocker impacts (2018), and machine learning adoption in digital marketing (2019). Projects: Principal investigator for PMVP I-17-106-00 on programmatic buying challenges, and contributor to VEGA and KEGA grants related to influencer marketing and digital education.

• Generative AI
• Optimization
• UAVs
• +2 more

Marek Ružička serves as an Assistant Professor at the Technical University of Košice (TUKE), where he teaches Stochastic Modeling and Data Analysis (SMaAD) and Modeling and Prototyping Systems (MaPS) across multiple laboratory sessions and lectures in buildings PK6, L9, and N9. His research spans Generative AI, Optimization, UAVs, 5G telecommunications, and Physical neural networks, with applications in engineering and data science. His research program emphasizes generative models for solving complex physical and engineering problems, particularly using GANs for data synthesis, trajectory correction, and system optimization. He bridges theoretical AI with practical implementations in UAV networks, aerodynamics simulation, and telecommunications infrastructure, demonstrating strong interdisciplinary connections between machine learning and physical systems. Analysis of his 2019-2024 publications reveals consistent focus on generative adversarial networks applied to UAV-based network optimization, physical system modeling (mass-spring systems, car aerodynamics), and data augmentation for mobility datasets. His work shows evolving specialization in deep learning integration with telecommunications (5G) and physical neural networks, with increasing emphasis on real-time optimization and energy efficiency. Scientific Awards: No scientific awards were mentioned in the provided text. Advising and Grants: The source material contains no information regarding graduate students, research grants, or funded projects.

• Digital Image Processing
• Signal Processing
• Soft Computing
• +5 more

Prof. Annamária Várkonyiné Kóczy is a Professor at the Department of Informatics within the Faculty of Economics and Informatics at J. Selye University. She holds a joint appointment as a professor at Óbuda University's Institute of Software Design and Software Development. Her academic journey includes: Electrical Engineering studies (Measurement and Control) at Technical University of Budapest (1975-1981) Mechanical Engineering degree (Mechanical Engineer-Teacher) from the same institution (1978-1983) PhD in Computer Science from Technical University of Budapest (1996) DSc (Doctor of Sciences) from Hungarian Academy of Sciences (2010) Habilitation from Széchenyi István University (2017) Her research spans digital signal processing, soft computing, and hybrid techniques for complex systems, with applications in medical diagnostics, intelligent control, and sustainable technologies. She leads projects in computational intelligence and has developed novel algorithms for real-time processing in resource-constrained environments. Recent publications demonstrate strong focus on AI-driven solutions: machine learning for bioacoustic analysis (beehive swarming), fuzzy logic optimizations for edge computing, medical imaging diagnostics (COVID-19 detection), and sustainable energy control systems. Her work consistently bridges theoretical models with practical implementations in healthcare, environmental monitoring, and industrial diagnostics. She has secured multiple research grants including: OTKA K 105846: Intelligent Space and robotics (2012-2017) OTKA K 78576: Intelligent techniques in signal/image processing (2009-2013) GVOP-3.3.1: Intelligent 3D modeling systems (2006-2007) EU Structural Funds projects on vehicle industry collaborations She mentors graduate researchers in applied informatics and leads international collaborations across Europe and Asia, focusing on intelligent systems development.

Milan PokornýView profile

Associate Professor

• Graph Theory
• Integral Graphs
• Discrete Mathematics
• +3 more

Milan Pokorný is an Associate Professor at the Department of Mathematics and Informatics, Faculty of Education, University of Trnava in Trnava. His academic career spans over two decades, with significant contributions to graph theory and mathematical education. He actively engages in research, teaching, and educational technology development. His research interests include Graph Theory Integral Graphs Discrete Mathematics Mathematical Education Algorithm Complexity Statistical Data Processing The majority of his publications focus on spectral properties of graphs and educational methodologies. His work explores integral complete multipartite graphs, distance energy of graphs, and blended learning approaches in mathematics education. Milan Pokorný teaches courses in descriptive statistics, algorithm complexity theory, mathematics for natural sciences, financial mathematics, and technology integration for mathematics educators. He provides supporting materials for various subjects and maintains regular consultation hours for students.

Ivan BrezinaView profile

Professor

• Quantitative Economics
• Operational Research
• Economic Modeling
• +3 more

Ivan Brezina is a Professor and Dean at the Faculty of Economics and Business, Paneuropean University PEVŠ, where he also heads the Institute of International Business. His research focuses on the application of quantitative methods in economic practice, particularly operational research and optimization techniques. His recent work spans topics in computational economics, including ant colony optimization for solving the Traveling Salesman Problem, preference ranking methods for EU country comparisons, and dynamic portfolio models . He explores macroeconomic simulations using panel data and analyzes cybersecurity risks in financial systems. Key subfields of his research include algorithm design, macroeconomic modeling, investment policy, and financial risk analysis. His publications often bridge economics with computer science and operations research.