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• Grid Computing
• Parallel Computing
• Cloud Computing
• +4 more

Vladimír Siládi, PhD, serves as Assistant Professor and Head of the Department of Computer Science at Matej Bel University in Banská Bystrica, Slovakia, where he has held academic positions since 1995. His current roles include Project Coordinator for the Virtual University initiative and Registration Authority for SlovakGrid, with prior experience as a part-time Assistant Professor at Slovak University of Technology. Educational Background: PhD in Computer Science, Slovak University of Technology in Bratislava (1997-2007) Master's in Theology, Comenius University in Bratislava (2003-2008) Master's in Secondary Education and Teaching (cum laude) and PaedDr. (EdD), Matej Bel University (1988-1993, 2005) High School Diploma, GMN Banská Štiavnica (1984-1988) His research centers on Grid Computing architectures , parallel processing techniques , and security frameworks for distributed systems . Specialized expertise includes GPU-accelerated algorithms for NP-hard problems, trust models in ad hoc grid environments, and cloud-based educational platforms. His interdisciplinary work bridges computer science with environmental modeling and psychological applications through virtual reality systems. Publication analysis reveals a consistent focus on computational optimization across 12 major works (2006-2014), with recent contributions emphasizing trust intersection models for decentralized grids (2012-2013) and cloud-based educational infrastructure (2013). Earlier works established foundations in GPU-accelerated network topology optimization and genetic algorithms for irregular systems (2006-2010). Scientific Awards: No awards documented in source materials Project leadership includes the Virtual University of Matej Bel University (ITMS 26110230077) coordinating 85 team members across 280 courses, plus TEMPUS-FLACE distance learning development (1998-2000). His registration authority role for SlovakGrid since 2009 supports national research infrastructure. Departmental leadership involves managing the Computer Science team while teaching core courses in algorithms, grid technologies, and GPU programming, maintaining consultation hours for student engagement.

• Parallel Programming
• GPU Programming
• Image Processing
• +5 more

Sándor Szénási is a Professor at the Department of Informatics within the Faculty of Economics and Informatics at J. Selye University, where he serves as the person responsible for the Applied Informatics study program. With over two decades of academic experience, he has established himself as a leading researcher in parallel programming, GPU programming, and image processing, with recent expansion into machine learning applications. Eötvös Loránd University, Faculty of Science and Informatics (2001-2004): Information technology teacher Budapest Polytechnic, John von Neumann Faculty of Information Technology (1997-2001): B. Engineer in Information Technology Óbuda University (2010-2013): PhD in Applied Informatics Habilitation at Óbuda University (2019): Information Science and Technology Professor inauguration at Óbuda University (2022) Szénási's research spans computational methods with practical applications across multiple domains. His early work focused on parallel and GPU programming for image segmentation and heat transfer simulation. More recently, he has integrated machine learning techniques with traditional computational approaches, particularly in metaheuristic optimization, speech processing, and inverse problem solving. His interdisciplinary research bridges computer science with transportation safety, manufacturing, and medical applications. His recent publications reveal a clear evolution toward hybrid computational approaches that combine machine learning with traditional algorithms. There is a strong emphasis on optimization techniques, particularly metaheuristics enhanced with machine learning components. His work spans diverse application areas including speech emotion recognition, autonomous vehicle control, additive manufacturing, and heat transfer simulation, while maintaining a core focus on computational efficiency and parallel processing. Szénási has been actively involved in multiple EFOP-funded research projects including 'Improvement of higher education institutes for better teaching quality and accessibility,' 'Dynamics and control of autonomous vehicles,' and 'Solving the Inverse Heat Conduction Problem with Machine Learning.' His collaborative work with researchers like Gábor Kertész, Zoltán Vámossy, and Imre Felde demonstrates his commitment to interdisciplinary research.

• 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.

Alfredo Daniel SanchezView profile

Researcher

• Physics
• Optics
• Nonlinear Optics
• +5 more

Alfredo Daniel Sanchez, PhD, is a Researcher at the Joint Glass Centre (Vitrum Laugaricio – VILA) within the FunGlass Centre for Functional and Surface Functionalized Glass at Alexander Dubček University of Trenčín, Slovakia. He joined in January 2025 after serving as a Researcher at ICFO – The Institute of Photonic Sciences from January 2021 to December 2024. Education Sc. and M.Sc. in Physics from Universidad de Buenos Aires and CIBION, Argentina (2015). Thesis: Synthesis and Modeling of the Optical Properties of Gold Nanorods. PhD in Engineering from Universidad Nacional de Cuyo, San Carlos de Bariloche, Argentina. Thesis: Nonlinear effect in waveguides in the infrared region. Research Interests Dr. Sanchez's work spans Physics , Optics , and Nanomaterials , with core expertise in nonlinear optics , plasmonics , and computational modeling . His research focuses on waveguide nonlinearities, metal nanoparticle interactions, and GPU-accelerated simulations of electromagnetic phenomena. He develops theoretical frameworks for ultrafast optical processes and applies parallel computing to solve complex photonics problems. Publication Trends His 15 most recent publications (2020-2024) reveal a cohesive research program centered on nonlinear optical phenomena in waveguides and nanomaterials. Key themes include modulation instability mechanisms, optical parametric oscillator dynamics, and computational tools for second-harmonic generation. The work bridges theoretical modeling (e.g., photon-conserving nonlinear Schrödinger equations) with practical applications in nuclear waste immobilization and plasmonic biosensing, demonstrating interdisciplinary impact across photonics, materials science, and nuclear engineering. Scientific Awards PhD Scholarship by CONICET (April 2016) Best Poster at NANOINTI Conference (June 2013) Advising and Grants Dr. Sanchez has served as a reviewer for Optica Publishing Group (8 articles) and Physical Review (2 articles). His research is supported by the Horizon 2020 FunGlass project (grant agreement Nº739566), indicating significant European funding. While specific grant leadership isn't detailed, his involvement in multi-institutional projects demonstrates collaborative grant execution capabilities. Labs and Teams He operates within the Joint Glass Centre at Alexander Dubček University, a hub for glass science research under the FunGlass Centre. This unit maintains strategic partnerships with Friedrich-Alexander Universität Erlangen-Nürnberg, Friedrich-Schiller-Universität Jena, Consejo Superior de Investigaciones Científicas, and Università degli Studi di Padova, facilitating cross-border research in functional glass materials.