Find Academic Supervisors

• 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.

Martin AlexyView profile

Associate Professor

• Financial Econometrics
• Credit Risk Modeling
• Sovereign Credit Ratings
• +3 more

Martin Alexy is an Associate Professor at the Department of Finance within the Faculty of Economics and Finance at Bratislava University of Economics and Business. He also serves as Head of Section and Deputy Head of the Department for Science Development in the Business Finance Section. His research focuses on financial econometrics, sovereign credit ratings, enterprise failure prediction, and composite index construction. Alexy teaches courses such as 'Základy finančnej ekonometrie' (Basics of Financial Econometrics) and 'Riziko a neistota vo financiách' (Risk and Uncertainty in Finance). His research explores topics like sovereign credit rating determinants, machine learning applications in SME failure prediction, and total factor productivity analysis in Europe. Notable contributions include work on Altman’s Z’-Score models adaptation for Slovak SMEs and gender diversity in private firms. Alexy collaborates with institutions like the SecureDataLab and Bee4R LAB, focusing on behavioral economics experiments and data-driven financial analysis. His publications span journals like Studies in Economics and Finance , Ekonomický časopis , and Acta Oeconomica , with recent focus on machine learning applications in financial modeling and regional economic dynamics. No scientific awards are explicitly mentioned in the provided texts. Alexy’s advising and grant activities are not detailed here, but his research group actively participates in projects related to financial risk assessment and regional development. He contributes to the EAPG Working Paper Series and maintains academic partnerships through Erasmus agreements and framework collaborations.

• Electrical Engineering
• Automation
• Informatics
• +5 more

Martin Olejár serves as an Associate Professor at the Institute of Electrical Engineering, Automation, Informatics and Physics within the Faculty of Engineering at Slovak University of Agriculture in Nitra. His academic work focuses on the intersection of electrical engineering, automation systems, and agricultural applications. His research interests span multiple technical domains including robotics, machine learning, computer vision, and Industry 4.0 implementation in agricultural contexts. His recent work demonstrates a strong emphasis on applying advanced computer vision techniques to agricultural challenges. Professor Olejár has recently published research on tomato stem recognition using YOLOX technology, indicating his active engagement in cutting-edge computer vision applications for agriculture. His work shows a clear trend toward implementing machine learning solutions for precision agriculture problems. He serves as Deputy Project Leader for the KEGA project titled 'Implementation of technology of Industry 4.0 in education process in study program Control Systems in Production Engineering' (2021-2023), demonstrating his commitment to modernizing engineering education with contemporary technological approaches. His teaching and research activities position him at the forefront of applying advanced automation and informatics solutions to agricultural engineering challenges, particularly in the domains of computer vision and machine learning applications.

• Artificial Intelligence
• Wireless Communications
• Cognitive Radio Networks
• +4 more

Prof. Juraj Gazda is a Professor at the Faculty of Electrical Engineering and Informatics, Technical University of Kosice. His research focuses on cognitive radio networks, artificial intelligence, green communications, and agent-based modeling. He holds a PhD in engineering from TUKE (2010) and has extensive industry experience as an external consultant at Nokia Networks (2011–2014), advising on LTE wireless systems. He has been a guest researcher at institutions like Ramon Llull University (Spain), Technical University of Hamburg (Germany), and Delft University of Technology (Netherlands). His teaching includes stochastic modeling and data analysis courses. Gazda’s work bridges academia and industry, emphasizing network security, autonomous systems, and 6G technologies. Research highlights include contributions to UAV-assisted networks, blockchain-based spectrum management, and AI-driven edge computing. His projects address real-world challenges in 5G/6G networks, including energy efficiency, secure communication, and autonomous vehicle coordination. Gazda actively collaborates with global tech firms like Verizon Wireless, contributing to network design and optimization. Publications span AI applications in healthcare, vehicular networks, and quantum computing. He advocates for interdisciplinary research, integrating machine learning, blockchain, and metaverse technologies to address future mobility and communication needs.

• Cybersecurity
• Multimedia Content Delivery
• IP Networks
• +5 more

Dr. Miroslav Michalko is an Associate Professor at the Department of Computer Networks and Security, Faculty of Electrical Engineering and Informatics, Technical University of Košice. His research focuses on Cybersecurity, Multimedia Content Delivery, IoT for eHealth, Smart Cities and Homes, Web Technologies, and EU Project Management. He teaches courses such as Computer Networks, Security of Computer Networks, and CCNA Security. He actively coordinates the Girls in IT @ FEEI TUKE initiative and serves as the National Guarantor for Information Technologies and Telecommunications within Slovakia's Qualifications Verification System. His research interests span Cybersecurity methodologies, IoT integration in healthcare, Smart City infrastructure, and innovative educational technologies. Notable projects include developing UAV-based monitoring systems, smart home solutions, and cybersecurity educational platforms. He has contributed to over 50 peer-reviewed publications, emphasizing practical applications of computer networks and IoT. Dr. Michalko's recent work highlights advancements in autonomous UAV control via machine learning, intrusion detection in IoT environments, and real-time water leak detection systems. His teaching emphasizes hands-on learning through simulations and industry-aligned certifications like Cisco's NetAcad program.

Marian MachView profile

Associate Professor

• Symbolic Artificial Intelligence
• Evolutionary Computation
• Ontological Engineering
• +5 more

Marian Mach is an Associate Professor at the Department of Cybernetics and Artificial Intelligence, Technical University of Kosice. He holds a Ph.D. (1992) and habilitation in Artificial Intelligence (2001). His research focuses on symbolic AI, evolutionary computation, knowledge modeling, and ontological engineering. He has led national and EU projects like Modermed (2023-2027) and DL4VISION (2022-2025), addressing toxic behavior detection and deep learning for image processing. Education: Ph.D. in Technical Cybernetics (1992), TU Kosice Habilitation in AI (2001), TU Kosice M.S. in Technical Cybernetics (1985), TU Kosice Research Interests: Evolutionary algorithms Constraint satisfaction problems Knowledge representation Machine learning applications in social media analysis Robotics and intelligent systems Teaching: Courses include Machine Learning II, Evolutionary Algorithms, and Application of Logic in Intelligent Systems. He has developed over 20 courses since 1987. Grants & Projects: EU-funded initiatives: VICINITY (2016-2019), PICASO (2016-2019) National grants: APVV-22-0414 (2023-2027), VEGA 1/0394/22 (2022-2025) Labs/Teams: Involved in AI Center at TU Kosice and collaborative projects on cloud-based robotics and semantic web technologies.

• Econometrics
• Mathematical Economics
• Causal Inference
• +3 more

Lukáš Lafférs is an Associate Professor at the Department of Mathematics, Faculty of Economics, Matej Bel University. He holds a PhD in Economics from NHH Bergen (2014) and a Doc (2024) from Masaryk University Brno, alongside an Mgr. from FMFI UK Bratislava (2009). Education: Doc (2024), PhD (2014), Mgr. (2009) Academic Rank: Associate Professor Affiliation: Department of Mathematics, Faculty of Economics, Matej Bel University Contact: Lukas.Laffers@umb.sk His research spans Econometrics , Mathematical Economics , and interdisciplinary Medical Research . Key areas include causal inference, partial identification, machine learning applications in econometrics, and clinical studies on liver diseases. Recent work focuses on double machine learning methods, treatment effect estimation, and healthcare outcomes analysis. Scientific contributions include an Editor’s choice article in the Econometrics Journal (2022) and collaborations on clinical research in hepatology. His publications reflect a blend of econometric theory and applied health economics, particularly in alcohol-associated hepatitis studies.

• Geoinformatics
• Geographic Information Systems
• Spatial Databases
• +5 more

Assoc. Prof. Renata Ďuračiová, PhD., serves as Associate Professor and Head of the Department of Global Geodesy and Geoinformatics at the Faculty of Civil Engineering, Slovak University of Technology in Bratislava. Her academic role centers on advancing geoinformatics through rigorous research in spatial data quality, uncertainty modeling, and mathematical GIS methodologies while leading departmental operations and curriculum development. Her research spans spatial databases, geospatial analyses, and environmental applications including Lidar processing, building footprint detection, and solar radiation modeling. Key contributions address bark beetle infestation prediction using satellite data and machine learning, alongside innovations in fuzzy logic for spatial database querying and heterogeneous data integration. Her work bridges theoretical geoinformatics with practical solutions for forest management and urban planning challenges. Analysis of her 2017-2025 publications reveals consistent focus on spatial data quality assessment, terrain parameter effects on environmental modeling, and algorithmic development for Lidar/satellite data processing. Recurring themes include uncertainty quantification in spatial analyses, cross-source data integration (e.g., OpenStreetMap/INSPIRE), and climate-driven ecological modeling. Her technical expertise manifests in specialized tools like point-cloud solar radiation calculators and predictive models for forest disturbances. Prof. Ďuračiová actively contributes to the geospatial community through leadership roles in the Cartographic Society of the Slovak Republic (Executive Committee since 2011) and Slovak Association for Geoinformatics (Presidency since 2011). Her professional engagement emphasizes advancing geoinformatics standards and applications within Central European contexts while mentoring through courses like Database Systems in GIS and Geodata Quality Analysis.

Tibor KmeťView profile

Professor

• Applied Informatics
• Neural Networks
• Mathematical Modeling
• +5 more

Professor Tibor Kmeť is a distinguished academic at J. Selye University's Faculty of Economics and Informatics, where he serves as a Professor in the Department of Informatics. He has been affiliated with the university since 2006 and holds significant responsibilities as the person responsible for multiple study programs including Teaching of Informatics, Applied Informatics, and Theory of Teaching Mathematics and Informatics. Dr. Kmeť completed his higher education at Comenius University in Bratislava, where he earned his degree in Mathematics from the Faculty of Science (1975-1980), followed by rigorous examinations (1981), doctoral studies (1984-1987), and habilitation (1996), all in Mathematics. In 2006, he completed his professorial inauguration at Constantine the Philosopher University in Nitra in the Theory of Mathematics Education. His research spans multiple domains at the intersection of mathematics, computer science, and education. Professor Kmeť has made significant contributions to neural network applications in solving complex mathematical problems, particularly in optimal control theory and epidemiological modeling. His work on applying computational methods to educational contexts, especially in mathematics education, demonstrates his commitment to bridging theoretical research with practical applications. He has also conducted important research in geometry education, developing methods for visual explanation in dynamic geometry environments. An analysis of his recent publications reveals a consistent focus on applying neural networks and computational methods to solve complex mathematical problems. His research trajectory shows progression from foundational work on neural network solutions for optimal control problems to more applied work in epidemiological modeling and educational technology. The interdisciplinary nature of his work is evident in publications spanning computer science, mathematics, epidemiology, and education journals. Professor Kmeť has successfully led multiple research projects including 'Digital Smart Household' (2019-2020), 'Creation of 3D Model Based on Drone Photographs Using Photometric Method' (2019-2021), and 'Modeling Stock Market Rates Using Neural Networks' (2020-2021), demonstrating his ability to secure research funding and lead projects with practical applications. His academic career includes previous positions at Constantine the Philosopher University in Nitra (1992-2017) and the Institute of Experimental Biology and Ecology SAS Bratislava (1980-1992), where he served as an independent scientific worker and researcher. This diverse background has informed his interdisciplinary research approach that combines mathematical rigor with practical applications in various domains.

Ondrej TakáčView profile

Associate Professor

• Navigation of Mobile Robots
• Image Processing
• Didactics Informatics
• +2 more

Ondrej Takáč, PhD is an Associate Professor and Head of the Department of Informatics at the Faculty of Economics and Informatics, J. Selye University. He has been actively contributing to academia since 2012, advancing from Senior Lecturer to his current position as Associate Professor in 2023. His leadership extends beyond teaching as he serves in multiple administrative roles including CEEPUS Local Coordinator for Engineering as Communication Language in Europe since 2012, Member of the Faculty Senate since March 2021, and Member of the Quality Assurance Board since November 2021. His educational background includes dual degrees from Slovak University of Agriculture in Nitra: a degree in Agricultural Engineering from the Faculty of Engineering (2008-2012) and Supplementary Pedagogical Studies from the Faculty of Economic (2010-2012). He completed his PhD in Transport Machinery and Equipment at the Technical Faculty of Slovak University of Agriculture (2008-2012). Takáč's research focuses on three primary areas: Navigation of Mobile Robots, Image Processing, and Didactics Informatics. His work bridges theoretical computer science with practical educational applications, particularly through the development of animation-simulation models for educational purposes. His research demonstrates a consistent trajectory toward increasingly sophisticated educational technologies, culminating in current work on intelligent animation-simulation models for deep learning applications. His publication portfolio shows significant productivity with 116 total publications including 56 scientific outputs (28 book chapters and 28 journal articles), 8 professional outputs, and 47 other monitored publications. His work has garnered 189 citations, with 24 appearing in citation indexes, indicating growing international recognition of his contributions to educational technology and informatics. In his administrative capacity, Takáč serves as Study Advisor for the master's degree program Applied Informatics since 2022, and as of 2024, he has joined both the Commission for the Doctoral Study Program in Teaching Theory of Mathematics and Informatics and the Disciplinary Committee for Students at the Faculty of Economics and Informatics. His grant activity centers around KEGA projects focused on educational simulation models, with continuous funding from 2011 through 2024. Takáč leads the Department of Informatics and has been instrumental in developing educational simulation resources. His ongoing research projects suggest a strong commitment to advancing deep learning applications in educational contexts, with the most recent project (014TTU-4/2024) focusing on intelligent animation-simulation models for deep learning environments.

• Machine learning algorithms
• Image processing optimization
• GPU programming
• +5 more

László Marák is an Assistant Professor at the Department of Informatics, Faculty of Economics and Informatics, J. Selye University. His academic career spans machine learning, image processing, and computational optimization. Research focuses on GPU-based machine learning algorithm optimization Developed novel calibration methods for camera lens parameters Explored secure electronic voting protocol design His work combines theoretical advancements with practical industrial applications in computer science and artificial intelligence domains.

Michal TkáčView profile

Professor

• Quantitative Methods
• Business Economics
• Quality Management
• +5 more

Michal Tkáč is a Professor at the University of Economics in Bratislava , serving as the Dean of the Faculty of Business Economics with seat in Košice . He is affiliated with the Department of Quantitative Methods , where his work emphasizes the application of quantitative techniques and algebraic structures in business economics and quality management. Research Focus: Quantitative methods, quality management, graph theory, machine learning, and financial analytics. Projects: Led initiatives like "Technical and Economic Analysis of Coal Replacement" (2020), coordinated H2020 projects, and VEGA grants for AI in bond markets. His recent publications span topics such as population health in EU regions , neural networks in business , and environmental engineering . Key trends include integration of AI into economic modeling, graph-theoretic approaches to structural problems, and sustainability research. Michal Tkáč is a prominent member of international networks like the European Network for Business and Industrial Statistics (2007–present) and has held leadership roles in Slovak quality and statistical societies.

• Digital Marketing
• E-Commerce
• Cognitive Systems in Marketing
• +3 more

Peter Červenka is an Assistant Professor in the Department of Marketing at Bratislava University of Economics and Business, Faculty of Commerce. His work bridges digital marketing, e-commerce, and cognitive technology applications in business analysis. Research focuses on AI-driven marketing, augmented reality in education, and SEO optimization. Active in interdisciplinary projects, including EU consumer policy and regional tourism strategies. Recent publications highlight his contributions to digital marketing tools, cognitive systems in consumer analysis, and augmented reality in e-learning. Notable projects include VEGA grants on product design and consumer behavior, as well as HP initiatives on web optimization.

Michal PitoňákView profile

Associate Professor

• Quantum Chemistry
• Computational Chemistry
• Non-covalent Interactions
• +3 more

Assoc. Prof. Michal Pitoňák serves as Associate Professor and department website administrator at the Department of Physical and Theoretical Chemistry, Faculty of Science, Comenius University in Bratislava. His research focuses on quantum chemistry methodology development with applications in non-covalent interactions and computational efficiency, supported by VEGA research project 1/0777/19. His core research areas include: Quantum Chemistry and Theoretical Chemistry Non-covalent Interactions in molecular systems Approximate quantum-chemical method development High-Performance Computing optimization Parallel programming for computational chemistry Chemical reactivity modeling Analysis of his 2009-2019 publications reveals consistent advancement in non-covalent interaction modeling, progressing from fundamental method validation (2009-2010) to large-system benchmarking (2013) and computational optimization (2018-2019). His work bridges quantum chemistry theory with high-performance computing to solve computationally intensive chemical problems. No scientific awards were documented in the source material. Prof. Pitoňák leads research project VEGA-1/0777/19 on advanced numerical mathematics and programming. The provided information does not indicate any graduate student supervision. He operates within the Department of Physical and Theoretical Chemistry, which conducts fundamental research in quantum chemistry, molecular modeling, and computational methodology development at Comenius University's Bratislava campus.