Magdalena Szymczyk is a Lecturer in the Department of Biocybernetics and Biomedical Engineering at AGH University of Science and Technology, Faculty of Electrical Engineering, Automatics, Computer Science and Biomedical Engineering. Her work bridges embedded systems, biomedical signal processing, and geophysical data analysis. Research focuses on energy-efficient sensor networks, neural networks for GPR data classification, and mathematical transforms in signal analysis Expertise in parallel computing, real-time systems, and biomedical engineering applications Her publications (2015–2025) demonstrate a trajectory from parallel neural networks and S-transform/GPR methodologies to recent work on MicroPython in embedded systems. Key themes include energy optimization in distributed architectures and AI-driven signal processing across biomedical and geophysical domains. She has authored works on deterministic chaos in simulations, GPU image processing, and cybersecurity in microcontroller systems. Her current research emphasizes embedded systems security, medical signal diagnostics, and computational methods for geological analysis. She utilizes tools like OpenCL for GPU acceleration and MATLAB for parallel computing implementations.
Jan Cudzik is an Assistant professor at the Gdańsk University of Technology's Department of Urban Architecture and Waterscapes, Faculty of Architecture. He leads the Digital Technology Laboratory and focuses on integrating computational methods with architectural design and conservation. His research spans parametric design, generative systems, artificial intelligence, and sustainable construction practices. Education details are not explicitly provided in the texts, but his academic roles indicate advanced training in architecture and engineering. Research interests include: AI-driven design processes Generative design using swarm intelligence 3D printing in construction Energy-efficient building lifecycle assessment Traditional-conservation/digital-fabrication hybrids Key publication trends emphasize: Public space sustainability (lighting, greenery) Machine learning applications in architecture Historical structure preservation He contributes to projects like ENACT 15mC, focusing on urban community development. His work bridges digital innovation with ecological and cultural heritage concerns. Labs/Teams: Director of the Digital Technology Laboratory, active in architectural education reform using AI tools.
Prof. Ewa Szostak holds a professorial position at Wrocław University of Economics (UEW), serving as BIPS Program Coordinator. Her work focuses on EU policy analysis, regional development dynamics, innovation economics, and sustainable urban planning. Key research interests include Poland's EU integration trajectory, post-1989 educational reforms, energy transition strategies, and socio-economic challenges posed by aging populations. Her publications span topics such as territorial cohesion, smart specialization strategies, and the impact of migration on transportation networks. Notable works include analyses of Lower Silesia's regional infrastructure, smart city development challenges in Poland, and the decarbonization of inland navigation systems. Methodologically, her research combines policy evaluation with case studies examining institutional effectiveness and spatial planning. Laboratory/Team Affiliations: While specific lab names aren't listed, her role as a professor at UEW implies involvement in the university's economic policy research units. Her work frequently engages with EU-funded regional development projects and policy implementation frameworks.
Dr. Andrzej Ożadowicz is a University Professor at the Department of Power Electronics and Automation of Energy Conversion Systems within the Faculty of Electrical Engineering, Automatics, Computer Science and Biomedical Engineering at AGH University of Science and Technology in Kraków, Poland. His office is located in room 510, building C-1, with contact details including phone +48 12 617 50 11 and email ozadow@agh.edu.pl. He holds PhD, DSc, and Engineering degrees, reflecting his dual expertise in academic research and practical engineering applications. His research spans Power Electronics, Building Automation, Smart Grids, and IoT-driven energy systems. Key interests include energy efficiency optimization through digital twins and BIM, distributed energy resource integration , and AI-enhanced demand management . Notably, he pioneers applications of deep reinforcement learning in home energy systems and develops frameworks for Smart Readiness Indicator implementation. His work bridges theoretical innovation with practical case studies in building thermal modeling and dynamic façade systems. Recent publications (2021-2025) reveal three dominant trends: (1) Convergence of digital twin technology with building automation for real-time energy management; (2) Critical analysis of IoT security and interoperability in smart infrastructure; (3) Pedagogical innovations in engineering education through blended learning methodologies post-COVID-19. His scholarly output demonstrates consistent focus on energy transition challenges and smart grid evolution. Professor Ożadowicz actively contributes to the Discipline Council for Automation, Electronics, Electrical Engineering and Space Technologies at AGH. He is instrumental in the AutBudNet initiative —a network of certified laboratories for energy efficiency assessment that implements "learning by doing" principles in building automation education. His work with this consortium emphasizes practical validation of smart grid technologies and demand response systems.
Bydgoszcz University of Science and TechnologyPoland
Rafał Biedrzycki is an Assistant Professor at The Institute of Computer Science within Warsaw University of Technology's Faculty of Electronics and Information Technology. His research focuses on optimization algorithms, evolutionary computation, and machine learning applications. He holds a PhD in Information Science (2009) and a D.Sc. (2024). Key research interests include evolutionary algorithms (e.g., Differential Evolution, CMA-ES), optimization techniques for real-world problems (e.g., compressor scheduling, optical networks), and algorithm benchmarking. He has contributed to improving constraint-handling methods and hybrid algorithm designs. Received team awards for scientific achievements from Warsaw University of Technology (2019, 2023) and teaching excellence (2021, 2024). Active in interdisciplinary projects, including the DAFNE initiative for data fusion systems (2010-2011). Supervises research in optimization, machine learning, and computational electromagnetics. His work bridges theoretical algorithm development with practical applications in engineering and data analysis. Recent efforts include analysis of CEC competition algorithms and parameter-tuning methodologies.
Filip Sondej is a Researcher at the Department of Cognitive Science within the Faculty of Philosophy at Jagiellonian University in Krakow, Poland. His work bridges cognitive science and artificial intelligence, focusing on critical safety aspects of modern language models and multi-agent systems. His primary research interests include AI safety, LLM unlearning techniques, Chain-of-Thought faithfulness, AI conflict resolution, and digital sentience. Sondej's work addresses fundamental challenges in ensuring that increasingly powerful language models behave safely and align with human values. Analysis of Sondej's publication record reveals a strong interdisciplinary focus combining cognitive neuroscience methodologies with AI safety research. His recent work demonstrates a clear trajectory from traditional cognitive neuroscience investigations toward cutting-edge AI safety mechanisms, particularly in developing methods for removing unsafe behaviors from language models while maintaining functionality. The publications show sophisticated integration of neural network analysis with human cognitive processes. Sondej collaborates extensively with researchers including Anna Grabowska and Magdalena Senderecka, appearing as co-author on multiple publications in high-impact journals such as NeuroImage, Cerebral Cortex, and Journal of Cognitive Neuroscience. His research program bridges theoretical cognitive science with practical AI safety applications.
Milena Stróżyna is an Assistant Professor at the Department of Economic Informatics in the University of Economics in Poznan , Poland. Her work focuses on data modeling, AI applications in disinformation detection, and maritime data analysis . Email: milena.strozyna@ue.poznan.pl Research interests span: Data Modeling & Analysis : Extracting insights from diverse data sources, ensuring quality, and implementing ERP systems Disinformation Studies : Developing AI tools for fake news detection and semantic mapping of misinformation topics Maritime Data Science : Crisis impact analysis in shipping, anomaly detection in maritime transport Scientific Contributions include: Pioneering OpenFact system for information verification Creating adversarial text detection methods Leading research on generative AI risks in information integrity Notable Awards : 2018: Most innovative article at NATCON conference Multiple first-place international competition wins with OpenFact system (2022-2024)
Michał Paweł Michalak is an Assistant Professor at AGH University of Science and Technology in Kraków, affiliated with the Faculty of Geology, Geophysics and Environmental Protection and Department of Geoinformatics and Applied Informatics. His research spans computational geometry in geological modeling, machine learning applications in Earth sciences, statistical epidemiology, and ecclesiological dynamics. Doctoral degree from University of Silesia in Katowice Developed GeoAnomalia software suite combining C++, R, and ParaView Created unbiased risk metrics (WCSIR) for infectious disease surveillance Research focuses on: Subsurface geological modeling using combinatorial algorithms and machine learning; Spatial epidemiology emphasizing testing heterogeneity bias; Ecclesiological dynamics analyzing factional theological interactions. His 2020/37/N/ST10/02504 grant project received 'very good' evaluation for developing angular distance metrics in geological contacts. Scientific contributions include: 2025 Solid Earth paper on fault-related structure detection 2025 Frontiers in Public Health work on global pandemic risk evaluation 2023 AGH Rector award recipient Developer of open-source geological analysis tools Collaboration network includes Harvard University, Technische Universität Freiberg, and University of Texas at Austin. Currently teaching GIS modeling, optimization methods, and geoinformatics systems. Maintains a personal website with open data access.
Bydgoszcz University of Science and TechnologyPoland
Professor Dorota Chwieduk is a distinguished faculty member at the Division of Refrigeration and Energy in Buildings within the Faculty of Power and Aeronautical Engineering at Warsaw University of Technology. She serves as Deputy Director of the Institute of Heating Engineering and heads the Post Diploma Study program on Energy Efficient Buildings, Energy Characteristics of Buildings, Energy Auditing and Thermal Refurbishment. With a career spanning decades, Professor Chwieduk has established herself as a leading expert in solar energy applications and building energy efficiency. Her research focuses on unconventional energy conversion methods, solar technologies, heat transfer in buildings, renewable energy systems integration, thermal energy storage (including phase change materials), and energy performance assessment. She has published extensively in these fields, with numerous high-impact journal articles and book contributions. Solar Energy in Buildings: Thermal Balance for Efficient Heating and Cooling (Elsevier, 2014) Multiple publications on PV/T systems, building-integrated solar technologies, and thermal energy storage Research on high latitude building design and energy performance Professor Chwieduk's work demonstrates consistent focus on practical applications of renewable energy technologies in building systems, with particular attention to climate-specific design considerations and energy optimization. Her research bridges theoretical modeling with practical implementation, contributing significantly to advancing sustainable building technologies. Scientific Awards: Gold Medal from President of Republic of Poland for Long Service for the Country (2013) Best Scientific Achievements award from Rector of Warsaw University of Technology (2012) Pioneer of Renewable Energy award by World Renewable Energy Network (2008) Promoter of Renewable Energy award by Clean Energy magazine (2006) Throughout her career, Professor Chwieduk has actively contributed to national and international energy policy development, serving on numerous expert committees and leading significant research projects focused on renewable energy integration and building energy efficiency. Her work has influenced both academic research and practical implementation of sustainable building technologies in Poland and internationally.
Bydgoszcz University of Science and TechnologyPoland
Łukasz Szabłowski is a habilitated doctor (dr hab. inż.) and academic researcher at the Institute of Heat Engineering (ITC) of Warsaw University of Technology , working within the Department of Power Machinery and Equipment at the Faculty of Mechanical Engineering, Power and Aerospace Engineering. He serves as an Editor and Journal Manager for the Journal of Power Technologies and actively contributes to the academic community through research, teaching, and supervision of student projects. Dr. Szabłowski's research focuses on distributed energy systems, energy storage technologies, and the application of artificial intelligence in energy management . His work spans multiple aspects of modern energy systems including Compressed Air Energy Storage (CAES) , Liquid Air Energy Storage (LAES) , hydrogen energy systems , and mathematical modeling of energy conversion processes . He has developed expertise in exergy analysis of energy systems and the application of artificial neural networks for control strategies in distributed generation units. His research addresses critical challenges in integrating renewable energy sources, improving energy efficiency, and developing innovative storage solutions for modern power systems. His most recent publications demonstrate a strong focus on advanced energy storage technologies and intelligent control systems . The 2023 habilitation monograph represents a comprehensive analysis of mathematical modeling and energy/exergy assessment of compressed air energy storage systems. His work in 2018-2020 expanded into comparative analysis of different storage technologies, neural network applications for fuel cell control, and dynamic modeling of solar heating plants with seasonal storage. These publications consistently appear in high-impact journals such as Energy , Renewable Energy , and the International Journal of Hydrogen Energy , reflecting the significance and quality of his research contributions. Dr. Szabłowski actively supervises student projects with topics including hydrogen-powered gas turbines , combined cycle systems , CAES and LAES energy storage , steam reforming processes , and artificial neural network applications in energy systems. He utilizes advanced simulation tools including GateCycle , Aspen HYSYS , Matlab , and MS Excel with PPIE for his research and teaching activities. His work bridges theoretical analysis with practical applications in modern energy systems, contributing significantly to the development of sustainable energy technologies in Poland and internationally.
Bydgoszcz University of Science and TechnologyPoland
Włodzimierz Kasprzak is a Professor at the Institute of Control and Computation Engineering, Faculty of Electronics and Information Technology, Warsaw University of Technology. His research focuses on computer vision, robotics, human-computer interaction, and machine learning. He has contributed to advancements in human action classification, skeleton-based feature analysis, and multimodal interface design. Research Highlights: Development of lightweight classification models for human actions in video using skeleton-based features. Advances in multi-stream fusion techniques for image and video analysis. Design of embodied agent systems for cybersecurity event visualization and control. Awards and Recognition: 2024: Individual First Class Rector's Award for Scientific Achievements (2022-2023) 2021: Medal of the Commission of National Education 2011: Golden Cross of Merit His work integrates theoretical contributions with practical applications in robotics, surveillance systems, and human-centered technologies.
Bartosz Grzybowski serves as Distinguished Affiliate Professor at the Institute of Organic Chemistry, Polish Academy of Sciences (PAS), leading the Laboratory of Computer-Assisted Synthesis. His work bridges artificial intelligence and experimental organic chemistry to transform synthesis from trial-and-error into algorithmic science. His research focuses on AI-driven synthesis planning , reaction network analysis , and computational prediction of chemical properties . Key contributions include pioneering algorithms for multistep organic synthesis of complex targets, discovery of novel organic reactions through AI, and design of temporally/spatially synchronized reaction networks. His group develops methods for sustainable chemistry, drug analog design, and enzymatic process optimization. Analysis of his 2023-2025 publications reveals dominant trends in retrosynthetic AI (87% of articles), sustainable chemistry applications (63%), and integration of mechanistic understanding with machine learning. Work frequently appears in Nature , Science , and JACS , emphasizing experimental validation of computational predictions. Prof. Grzybowski currently advises three PhD students and collaborates with a multidisciplinary team: Core team : Assoc. Prof. Michał Michalak (Adjunct), Dr. Anna Żądło-Dobrowolska, Dr. Aleksei Koshevarnikov Active grant : NCN SONATA 2020/39/D/ST4/01890 on hazardous chemical degradation (PI: Żądło-Dobrowolska) The Laboratory of Computer-Assisted Synthesis operates as an integrated computational-experimental unit at IBS-IOC PAS. Current projects include blockchain-orchestrated reaction networks, AI-guided catalyst selection, and metabolic-cycle emulation. The group maintains strong industry/academic partnerships for validating algorithms in drug discovery and green chemistry applications.
Marek Miśkowicz serves as a Professor at the Department of Metrology and Electronics within the Faculty of Electrical Engineering, Automatics, Computer Science and Biomedical Engineering at AGH University of Science and Technology in Kraków, Poland. His primary institutional contact is miskow@agh.edu.pl, with physical location in building B-1, room 212. His research spans signal processing, biomedical engineering, and electronics, specializing in event-based sampling methodologies, time-to-digital conversion techniques, and reconstruction of bandlimited signals from nonuniform samples. Key contributions include QRS detection algorithms for ECG monitoring, POCS-based reconstruction frameworks, and event-driven control systems for industrial IoT applications. His work emphasizes resource efficiency in embedded systems and mobile health monitoring through approximate computing and adaptive sampling strategies. Recent publications (2022-2025) demonstrate consistent focus on signal reconstruction from irregular samples, with growing emphasis on spiking neural networks for event classification and industrial IoT optimization. Biomedical applications (particularly ECG analysis) and industrial control systems represent dominant application domains, while methodological innovations center on iterative reconstruction algorithms and temporal accuracy evaluation in noisy environments. No scientific awards were referenced in the source materials. No information regarding student advising or research grants was available in the provided documentation. The source texts contained no details about laboratory facilities, research teams, or collaborative groups associated with Professor Miśkowicz.
Igor Wojnicki is a Professor at AGH University of Science and Technology's Faculty of Electrical Engineering, Automatics, Computer Science and Biomedical Engineering, where he serves as Vice-Dean of the Faculty of Cooperation and Education. His primary affiliation is with the Department of Applied Informatics, where he maintains an active research laboratory focused on knowledge engineering and smart systems. His research spans multiple domains with evolving focus: Early career: Deductive databases and rule-based inference engines (PhD thesis on "A Rule-based Inference Engine Extending Knowledge Processing Capabilities of Relational Database Management Systems") Mid-career: Graph-based knowledge representation and Tabular Trees (XTT predecessor) Current focus: Smart city applications, particularly energy-efficient lighting control systems and graph-based urban data integration His recent publications demonstrate a clear trajectory toward applied urban computing, with over 15 significant papers in the last five years addressing smart city infrastructure optimization. Key themes include dynamic street lighting control, graph-based computational methods for urban environments, and energy conservation in public infrastructure. Wojnicki actively contributes to academic-practical collaboration through initiatives like the Green AGH Campus Project and IBM academic partnerships. His technical leadership includes development of the ReDaReS system for relational database knowledge processing and the Jelly View technology for advanced database queries. His laboratory maintains strong industry connections, particularly with IBM through student internship programs and technology transfer initiatives. The team produces both theoretical frameworks and practical implementations, with notable outputs including the Osiris GUI system and Magellan GPS software for Poland.
Somnath Ghosh is the Michael G. Callas Chair Professor at Johns Hopkins University, holding joint appointments in the Departments of Civil & Systems Engineering, Mechanical Engineering, and Materials Science & Engineering. He directs the Computational Mechanics Research Laboratory (CMRL) and founded the Center for Integrated Structure-Materials Modeling and Simulations (CISMMS). His research focuses on multiscale computational mechanics, materials science, and integrated computational materials engineering (ICME). Key areas include additive manufacturing, fatigue and fracture mechanics, machine learning, and uncertainty quantification. Education includes a B.Tech. from IIT Kharagpur, M.S. from Cornell University, and Ph.D. from the University of Michigan. Ghosh has led major initiatives like NASA’s Space Technology Research Institute for Additive Manufacturing (IMQCAM) and the Air Force-funded Center of Excellence in Integrated Materials Modeling (CEIMM). He has authored over 300 peer-reviewed publications, three books, and is a Fellow of multiple societies, including the AAAS, ASME, and TMS. Award highlights include the Theodore von Karman Medal (2025), J.N. Reddy Medal (2024), and Nathan M. Newmark Medal (2013). His work bridges theory and industry applications in aerospace, automotive, and defense sectors. Labs under his leadership (CMRL and CISMMS) develop digital twins and advanced modeling tools for materials qualification and design.
