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Łukasz ChabudzińskiView profile

Assistant Professor

• Hydrology
• Geographic Information Systems (GIS)
• Climatology
• +4 more

Dr. Łukasz Chabudziński serves as Assistant Professor at the Department of Hydrology and Climatology within the Faculty of Earth Sciences and Spatial Management at Maria Curie-Skłodowska University in Lublin. Employed since October 1, 2008, he earned his Doctor of Earth Sciences in Geography on March 30, 2016, following progressive roles from Assistant in the GIS Laboratory (2008-2016) to Assistant Professor positions. His educational background includes postgraduate studies in 'Management of research projects and development works' (2011-2012) and 'Research Project Manager' (2012-2013) at the University of Economics and Innovation in Lublin. Dr. Chabudziński's research focuses on hydrology, GIS applications, and climatology, with particular emphasis on groundwater resource analysis in southeastern Poland's Roztocze region and Lublin Upland. Analysis of his publication record reveals a strong interdisciplinary approach combining hydrology, geomorphology, and computational methods. His recent work increasingly integrates high-performance computing with traditional hydrological analysis, particularly examining spring dynamics, small water bodies, and geological influences on water resources in loess landscapes. Rector's Award (team, third degree) for organizing GIS Challenge (2017) Rector's Award (individual, third degree) for outstanding work for the University (2020) Dr. Chabudziński has supervised 22 diploma theses (21 bachelor's and 1 master's) with notable student successes in competitions like 'GIS Team' and 'GIS Challenge.' He serves as principal investigator for NCN grants and contributes to numerous research projects examining landscape evolution, hydrological processes, and archaeological site relationships in loess regions. He actively shapes geospatial education through leadership roles in academic conferences, competition organization, and curriculum development for geoinformatics programs, bridging theoretical research with practical applications in water resource management and environmental protection.

• Cryptography
• Computer Science
• High-Performance Computing (HPC)
• +3 more

Dr. Michał Klisowski is a Lecturer at the Fundacja Uniwersytetu Marii Curie-Skłodowskiej , affiliated with the Faculty of Mathematics, Physics and Computer Science and the Department of Information Systems Software . His research focuses on cryptography, high-performance computing, and media truth detection. Research Highlights: Cryptographic protocols, energy-efficient computation, media credibility analysis Email: michal.klisowski@mail.umcs.pl His recent publications address topics such as multicore key exchange protocols , RAPL power monitoring , and fake news detection using machine learning. He holds an ORCID identifier and has published in information and communication technology domains. Collaboration & Tools: Utilizes ORCID and Scopus for academic visibility, with a focus on integrating theoretical cryptography with practical computational efficiency.

• High-Performance Computing
• Matrix Factorization
• Multicore Processing
• +7 more

Dr. hab. Beata Bylina is a Professor at the Faculty of Mathematics, Physics and Computer Science , Maria Curie-Skłodowska University (UMCS) , affiliated with the Department of Information Systems Software . She specializes in high-performance computing, numerical methods, and energy-efficient parallel programming. ORCID ID : 0000-0002-1327-9747 Contact : beata.bylina@umcs.pl / beata.bylina@mail.umcs.pl Office : Room D-522 (Institute of Computer Science) or Room B-2, Akademicka Street 9, Lublin Consultations : Wednesdays 10:00–12:00 (in-person or remote via Microsoft Teams) Her research focuses on: Parallelization and vectorization techniques for multicore architectures Energy consumption optimization in numerical algorithms Matrix factorization methods (WZ, LU, QR) for CPU/GPU hybrid systems Markov chain modeling for network performance analysis Compiler optimization impact on performance and energy metrics Recent publication trends show emphasis on: Time-energy correlations in multithreaded algorithms OpenMP/OpenACC for hybrid CPU-GPU implementations Efficient sparse matrix storage schemes for GPUs Impact of hardware-specific optimizations (Xeon Phi, frequency scaling) Comparative studies of parallelization strategies