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Bogumiła HnatkowskaView profile

Assistant Professor

• Software Engineering
• Analysis and Design of Information Systems
• Software Development Methodologies
• +3 more

Dr. Bogumiła Hnatkowska serves as Assistant Professor at the Institute of Informatics within the Faculty of Computer Science and Management at Wrocław University of Science and Technology. Her academic career spans software engineering research and education with emphasis on model-driven approaches and quality assurance methodologies. Her research interests include: Software Engineering Analysis and Design of Information Systems Software Development Methodologies Model-Based Software Development Domain-Specific Languages Software Quality Recent publications (2021-2025) reveal concentrated research in model-driven engineering, business rules processing, and ontology integration. Key trends involve textual specification languages for use-cases, automated test generation mechanisms, and formal transformations for ontologies – demonstrating consistent application of theoretical rigor to practical software development challenges across agile and model-based contexts. Scientific Awards: No scientific awards were mentioned in the provided text Dr. Hnatkowska has served as principal investigator for multiple State Committee for Scientific Research grants including UML extensions for multimedia systems (2000), real-time systems analysis (2005), and model-driven database design (2008). Her teaching portfolio includes Software Engineering, Software System Development, and Advanced Programming Techniques courses where she supervises team projects providing students with hands-on development experience. She actively participates in partner programs including Visual Paradigm's Academic Training Partner Program (providing UML/BPMN/agile tools) and IBM Academic Initiative, supporting her research in software engineering methodologies and educational tool development.

• Cybersecurity
• Cryptography
• Information Security
• +7 more

Dr. Viktor Melnyk serves as an Assistant Professor in the Department of Applied Computer Science at the Institute of Mathematics, Informatics and Landscape Architecture within the Faculty of Natural Sciences and Technology at John Paul II Catholic University of Lublin. His academic activities span teaching, research, and extensive student supervision across multiple years. His research interests focus on cybersecurity, cryptography, and FPGA-based systems, with particular expertise in wireless network security (especially IEEE 802.15.4), hardware acceleration, and machine learning applications in electronic design. His work bridges theoretical computer science with practical security implementations, evident in his numerous publications and student thesis topics. Analysis of Dr. Melnyk's recent publications reveals a consistent focus on hardware security implementations, particularly for low-rate wireless networks and reconfigurable computing systems. His research trajectory shows increasing integration of machine learning techniques with traditional security protocols, reflecting broader trends in the field. The publications demonstrate both theoretical depth and practical implementation focus, with many papers addressing specific hardware implementations. Dr. Melnyk has served as an Independent External Expert for evaluating grant proposals in the European COST Open Call competition, indicating professional recognition of his expertise. His contributions to the academic community extend to reviewing numerous scientific articles across various domains including biomedical data processing, cyber-physical systems, and cloud computing. His academic advising is exceptionally active, with documentation of supervising over 100 diploma theses from 2015 through 2025 across both Bachelor's and Master's levels. The thesis topics consistently align with his research interests, covering cybersecurity, cryptography, network security, and hardware implementations. He teaches courses including 'Operating Systems,' 'Network Data Protection Technologies,' and 'Multimedia Systems,' with teaching materials adapted for remote delivery during the pandemic period.

• Outsourcing
• Offshoring
• Logistics
• +5 more

Katarzyna Budzyńska is a Researcher at the Department of Information Systems and Logistics within the Faculty of Economics at Maria Curie-Skłodowska University (UMCS) since 2017. She holds a PhD in Economics from UMCS (2016) and a Master's in Agribusiness from the University of Life Sciences in Lublin (2008). Her career spans affiliations with both the University of Life Sciences in Lublin (2009-2017) and UMCS (2014-present), where she led the PRELUDIUM VI grant on regional investment potential in BPO/SSC sectors. Education : PhD in Economics (UMCS, 2016); Master's in Agribusiness (University of Life Sciences in Lublin, 2008); Postgraduate Studies in Accounting (UMCS, 2009) Research Interests focus on outsourcing , offshoring , green logistics , and mobile banking . Her work examines the interplay between regional development , organizational strategies , and technological innovation . Recent publications address plastic waste management using machine learning and the legal dynamics shaping outsourcing enterprises in the EU. Scientific Contributions include over 15 peer-reviewed publications and participation in international conferences such as the MakeLearn & TIIM Joint Conference (Lublin, 2017) and the World Conference on Business, Economics (Antalya, 2016). Notable awards: 2020 UMCS Team Award for securing external funding and 2016 Individual Award for outstanding research.

Grzegorz J. NalepaView profile

Professor

• Artificial Intelligence
• Affective Computing
• Context-Aware Systems
• +9 more

Prof. Grzegorz J. Nalepa holds the position of Full Professor at the Faculty of Physics, Astronomy, and Applied Computer Science, Jagiellonian University, Poland. He leads the Jagiellonian Human-Centered Artificial Intelligence Lab and is involved in international projects such as the CHISTERA XPM initiative on explainable AI in predictive maintenance. His academic journey includes a PhD (2004), habilitation (2012), and a philosophy MA (2012). Research focuses on AI, affective computing, context-aware systems, and explainable AI (XAI). He has authored over 200 papers, two monographs, and edited volumes. Key projects include the BIRAFFE2 dataset for emotion-based personalization and the GEIST team's semantic wiki tools. Holds leadership roles in conferences (e.g., ECAI 2023) and serves on editorial boards of journals like Sensors and Intelligent Sensors Section . Awards include the 2018 Outstanding Monograph Prize and multiple AGH-UST Rector's Prizes for scientific achievements. Advises PhD and master students, supervising 36 MSc theses. Active in professional organizations like the Polish Alliance for AI and the IEEE Computational Collective Intelligence TC. His contributions span industrial collaborations, software tools (e.g., InXAI, LUX, KnAC), and international research networks.

• Environmental Chemoinformatics
• Nanotoxicology
• Predictive Modeling
• +5 more

Professor Tomasz Puzyn is affiliated with the University of Gdańsk , where he serves as Head of the Laboratory of Environmental Chemoinformatics within the Faculty of Chemistry and the Department of Environmental Chemistry and Radiochemistry. His research focuses on advancing predictive models for nanomaterial and chemical safety through chemoinformatics, machine learning, and Adverse Outcome Pathways (AOPs). Research Interests: Environmental Chemoinformatics Nanotoxicology QSAR/QSPR Modeling Machine Learning in Risk Assessment Endocrine Disruption Mechanisms Safe-by-Design Nanomaterials Recent Work Trends: Development of in silico New Approach Methods (NAMs) for nanomaterial genotoxicity and endocrine disruption Integration of transcriptomic data with AOPs for predictive toxicology Adsorption mechanisms of PFAS using modified biochar and metal oxides Quantum chemistry applications for environmental fate prediction Machine learning frameworks for drug delivery nanocarriers Harmonization of data reporting for regulatory acceptance Laboratory: Laboratory of Environmental Chemoinformatics Collaborative projects: CompSafeNano, HBM4EU

• Statistics
• Econometrics
• Supply Chain Management
• +7 more

Dr. Anna Tatarczak is a Lecturer at the Department of Management Research Methods, Institute of Management and Quality Sciences, Faculty of Economics, Maria Curie-Skłodowska University. She holds a PhD in mathematical sciences from Jagiellonian University (2015) and an MSc in mathematics from Maria Curie-Skłodowska University. Her 13-year career spans research and education in statistics, econometrics, logistics, and decision analysis. PhD: Jagiellonian University (2015) MSc: Maria Curie-Skłodowska University (original text suggests Master of Science) Specialized in data analysis and project management through additional postgraduate studies Her research focuses on quantitative methods in management, particularly game theory approaches for supply chain coalitions, profit allocation models, and horizontal collaboration in logistics. She has led multiple research projects including "Coordination of supply chains: a game theory approach" (2020-2022) and commercial projects for companies like SOLVERIS and Innovative Engineering. Her academic output includes 27 publications with ministerial score 868, focusing on: Collaborative logistics Supply chain optimization Decision support systems Economic disparity analysis Energy consumption modeling Statistical applications in management She has implemented educational projects for children and youth, and served as expert for international entities including the State Education Development Agency (Latvia) and Horizon 2020. Her work combines rigorous mathematical approaches with practical industry applications.

Aleksandra KnapińskaView profile

Researcher

• Network Optimization
• Machine Learning
• Traffic Prediction
• +7 more

Aleksandra Knapińska is a doctoral researcher at the Wrocław University of Science and Technology, Faculty of Electronics, Photonics and Microsystems, Department of Computer Networks and Systems. She is an active member of multiple research teams including the Computer Networks Team, Machine Learning Team, and Advanced Data Analysis Methods Team. Her work is primarily associated with the MAAN project focused on optimizing multilayer application-aware networks. Her research interests center on network optimization , machine learning for traffic prediction , and multi-criteria optimization in optical and multilayer networks . She applies advanced data analysis and machine learning techniques to model and predict time-varying network traffic, particularly in backbone and optical networks. Her work bridges theoretical modeling with practical network performance evaluation. The most recent articles highlight a strong trend in using machine learning—especially ensemble and neural network models—for short-term and long-term network traffic forecasting. These publications emphasize challenges such as feature selection, bandwidth blocking, node failure resilience, and traffic fragmentation in spectrally-spatially flexible optical networks. The research is deeply applied, targeting real-world network performance improvements. Scientific profiles: Google Scholar ResearchGate ORCID: 0000-0003-2654-4893 She is involved in supervising diploma theses and has participated in international research collaborations, including an internship at Politecnico di Torino, Italy, under the InterDocSchool program. She has presented her work at major conferences such as GLOBECOM, ONDM, RNDM, and CNSM. Her PhD thesis, titled "Optimization of multilayer networks with time-varying traffic aided by traffic prediction", is supervised by Prof. Krzysztof Walkowiak, with Dr. Piotr Lechowicz as co-supervisor. She is part of ongoing research projects including: Dark-Box Optimization – Developing highly effective general-purpose optimizers Evolutionary methods for multi-criteria optimization with many criteria Advanced optimization of multi-layer application-aware networks (MAAN) Using multi-criteria optimization in classifier training for decision-making tasks

Jakub NowosadView profile

Researcher

• Spatial Association
• Information Theory
• Landscape Metrics
• +7 more

Jakub Nowosad is a researcher affiliated with Adam Mickiewicz University in Poznań and currently holding a prestigious Marie Skłodowska-Curie Actions Postdoctoral Fellowship at the University of Münster's Remote Sensing and Spatial Modeling group (August 2024-August 2026). His work bridges geography, computer science, and environmental science with a focus on spatial data analysis and machine learning applications. Nowosad's research interests center on spatial association methods, landscape metrics, information theory applications in geography, and spatial machine learning techniques. He has made significant contributions to developing and implementing computational methods for analyzing spatial patterns, particularly through R programming packages that address spatial autocorrelation challenges in machine learning. His work spans environmental monitoring, landscape ecology, and geospatial analysis with practical applications in understanding climate change impacts, forest fragmentation, and permafrost degradation. His publication record demonstrates a strong focus on methodological development in spatial data science, with numerous recent publications on spatial machine learning frameworks, computational landscape ecology, and specialized software tools. Nowosad's work shows a clear trajectory toward integrating advanced machine learning techniques with traditional spatial analysis methods to overcome limitations in spatial prediction and pattern recognition. Marie Skłodowska-Curie Actions Postdoctoral Fellowship (MSCA-PF) for the PRISM project (PReservation and RecognItion of Spatial patterns using Machine learning) Nowosad actively contributes to the open-source geospatial community through software development, including packages like spatialRF and contributions to spatial machine learning frameworks. His collaborative work spans multiple institutions including the University of Cincinnati, International Institute for Applied Systems Analysis, and various European research groups. He appears to be developing methodologies that will significantly impact how spatial patterns are recognized and preserved in environmental datasets, with applications ranging from Arctic landscape monitoring to forest conservation planning.

Sinan Tankut GülhanView profile

Assistant Professor

• Urban Sociology
• Turkish Urbanization
• Comparative Urban History
• +7 more

Dr. Sinan Tankut Gülhan is an Assistant Professor at the University of Zielona Góra's Institute of Sociology in Poland, where he applies a multidisciplinary approach to urban sociology. With expertise spanning Turkish urbanization processes, comparative urban history, and digital transformation in urban contexts, he bridges theoretical frameworks with practical applications in urban planning and policy. His research interests focus on the intersection of urban sociology and digital transformation, examining algorithmic decision-making in urban planning, digital inequality, housing market dynamics, 'smart city' initiatives, and the impact of digital platforms on urban mobility. Drawing from Henri Lefebvre's spatial theory, he analyzes how urban spaces are produced through political, economic, and social processes, with particular attention to Istanbul's historical development. Dr. Gülhan has expanded his methodological approach from qualitative to quantitative and computational techniques, utilizing statistical analysis (RStudio, SPSS), data science applications (Python, machine learning), digital research methods (web scraping, text analysis), and spatial analysis (QGIS). His publications reveal a consistent focus on urban political economy, historical urban development, and the evolving relationship between state power and urban space. Actively engaged in public sociology, he collaborates with community organizations, policymakers, and media outlets, organizing workshops for planners and advising municipal governments on technology implementation. His work on the 1960 Istanbul Housing Census visualization demonstrates his commitment to making historical urban data accessible for contemporary urban challenges.

• Artificial Intelligence
• Natural Language Processing
• Legal Informatics
• +5 more

Tomasz Pełech-Pilichowski serves as a Lecturer at the Institute of Computer Science within the Faculty of Computer Science at AGH University of Science and Technology in Kraków. He concurrently holds dual administrative leadership positions as Director of the AGH Recruitment Center and Rector's Representative for Recruitment, demonstrating significant institutional impact beyond his academic role. His research expertise spans artificial intelligence, natural language processing, and legal informatics with methodological foundations in deep learning and time series analysis. Recent work focuses on AI-driven solutions for legal text processing (text segmentation, hypertext law), educational technology (gamification, recruitment systems), and security applications (facial-age detection, anomaly identification). His interdisciplinary approach consistently bridges computer science with law, education, and environmental science through practical implementations. Analysis of his 2023-2025 publications reveals three dominant research trajectories: legal tech innovation (68% of output featuring text segmentation and regulatory automation), educational transformation (22% including gamified AI skill development), and security/environmental systems (10% covering IoT integration and pollution prediction). This progression shows increasing specialization in AI-NLP fusion techniques applied to domain-specific challenges, particularly within legal informatics where he has developed novel text recovery and visualization frameworks.

• Artificial Intelligence
• Machine Learning
• Data Mining
• +8 more

Jarosław Wąs is a Professor and Head of the Department of Applied Informatics at the Faculty of Electrical Engineering, Automatics, Computer Science and Biomedical Engineering, AGH University of Science and Technology in Kraków, Poland. His academic leadership extends to governance roles including the Senate, Faculty College, and Disciplinary Council for Technical Information Technology and Telecommunications. His research spans Artificial Intelligence, Machine Learning, and Data Mining with core expertise in Rough Sets theory. He develops computational models for crowd simulation and pedestrian dynamics critical for evacuation planning, and applies deep learning to renewable energy forecasting and health trajectory prediction. His work bridges theoretical computer science with practical applications in energy systems, healthcare analytics, and cosmic physics. Analysis of his 2023-2025 publications reveals interdisciplinary convergence: Rough Sets combined with cellular automata for crowd modeling, transformer networks for electronic medical records, and hybrid deep learning approaches for renewable energy forecasting. Key trends include zero-shot learning in healthcare, anomaly detection in cosmic data, and data-driven evacuation simulation with social group dynamics. No scientific awards are mentioned in available sources. Information regarding student advising and research grants is not provided in the source material. No laboratory or research team affiliations are specified in the available documentation.

Ewa ZaborowskaView profile

Associate Professor

• Wastewater Treatment
• Environmental Engineering
• Machine Learning Applications
• +5 more

Dr. Ewa Zaborowska is an Associate Professor at the Department of Sanitary Engineering within the Faculty of Civil and Environmental Engineering at Gdańsk University of Technology. Her research focuses on environmental engineering with particular emphasis on wastewater treatment processes, greenhouse gas emissions, and sustainable energy recovery from wastewater treatment plants. Her research interests span across several critical areas in environmental engineering: Advanced machine learning applications for predicting nitrous oxide emissions in wastewater treatment Biogas production optimization through anaerobic digestion processes Carbon footprint analysis of wastewater treatment facilities Energy recovery pathways from wastewater treatment processes Mitigation strategies for achieving net-zero carbon conditions in wastewater treatment plants Dr. Zaborowska's recent publications (2022-2023) demonstrate a strong focus on sustainability challenges in wastewater management, with particular attention to greenhouse gas emissions (CH 4 and N 2 O) and carbon footprint reduction strategies. Her work often involves comparative studies between different countries (particularly Poland and Finland in the Baltic Sea region) and explores innovative approaches for energy recovery from wastewater treatment processes. Her scientific contributions include: Development of algorithms for selecting appropriate machine learning models for environmental prediction tasks Investigation of low-temperature pretreatment methods for enhancing biogas production Systematic reviews of net-zero carbon strategies for wastewater treatment plants Comprehensive carbon footprint analyses of wastewater treatment facilities Dr. Zaborowska actively collaborates with researchers from various institutions on projects related to sustainable wastewater management and greenhouse gas mitigation. Her work contributes significantly to the advancement of environmentally sustainable practices in the wastewater treatment sector.

Emanuel GullView profile

Professor

• Quantum Physics
• Condensed Matter Physics
• Theoretical Physics
• +4 more

Professor Emanuel Gull is a theoretical physicist specializing in numerical methods for quantum many-body systems. He holds a professorship at the University of Warsaw's Faculty of Physics, where he relocated his laboratory from the University of Michigan to conduct research under an ERC Advanced Grant. His work focuses on predictive algorithms for simulating quantum materials, integrating quantum field theory, condensed matter theory, quantum Monte Carlo methods, applied mathematics, and machine learning. This interdisciplinary approach addresses phenomena like magnetism and superconductivity in materials critical to technologies such as MRI machines and electric car batteries. Professor Gull's ERC Advanced Grant, the first awarded to a foreign researcher hosted at the University of Warsaw, underscores the significance of his project. Collaborating with the Quantum Molecular Systems group at the Faculty, his methods support experimental advancements in ultracold matter research. His research aligns with the University's strategic focus on cutting-edge interdisciplinary science. His achievements include the prestigious ERC Advanced Grant, highlighting global recognition of his contributions. The project’s relocation of his laboratory reflects Warsaw's growing role as a hub for quantum research. Grants and institutional support from the University of Warsaw's BMPB office further enable his work, emphasizing collaboration and innovation. Professor Gull's research lab, now based in Warsaw, bridges theoretical and applied physics, fostering advancements in quantum technologies. His work exemplifies the intersection of fundamental science and technological application, with direct implications for energy storage and medical imaging technologies.

Grzegorz KorcylView profile

Assistant Professor

• Field Programmable Gate Arrays
• Data Processing on Programmable Logic Devices
• Real-Time Distributed Processing Systems
• +3 more

Grzegorz Korcyl, PhD, is an Assistant Professor at the Department of Information Technologies, Jagiellonian University in Kraków. He holds a PhD in Applied Computer Science from AGH University of Science and Technology (2015) and an MSc in Applied Computer Science from Jagiellonian University (2010). His research focuses on Field Programmable Gate Arrays (FPGAs), real-time distributed systems, and data acquisition technologies. He co-authored a chapter in the book *Modern Techniques for Computer-Aided Melanoma Diagnosis* (ISBN:978-953-307-571-6), contributing to medical imaging and diagnostic systems. He is involved in academic initiatives such as the Juna Network Academy (Juniper Networks Academic Alliance) and the Students Computer Laboratory, promoting networking education and software development. His work intersects computer engineering with healthcare applications.

• Fuel Cells
• Energy Systems
• CO2 Capture Technologies
• +3 more

Dr. Jarosław Milewski is a researcher at the Institute of Heat Engineering , Faculty of Mechanical Energy and Aviation, Warsaw University of Technology. His work focuses on advanced energy technologies with particular emphasis on fuel cells, CO2 capture, and hybrid power systems. Research Interests: Fuel cell system modeling (MCFC/SOFC) Hybrid energy conversion technologies CO2 capture and utilization Thermal energy storage optimization Computational fluid dynamics applications Decentralized energy systems Scientific Recognition: Laureate of "Naukowcy dla gospodarki Mazowsza" (2012) Minister's scholarship for young scientists (2011) Multiple Rector's Awards (2004-2009)