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.
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.
Adam Woźniak is a Professor and Vice-Rector for Development at Warsaw University of Technology (WUT), holding positions at the Faculty of Mechatronics and the Institute of Metrology and Biomedical Engineering. He earned a PhD in 2002, D.Sc. (habilitation) in 2011, and was promoted to full professor in 2017. His research focuses on advanced geometrical measurement techniques, coordinate metrology, quality engineering, and reliability of mechatronic systems. He has authored 2 books and over 130 scientific publications, including work on probing accuracy, X-ray CT applications, and dynamic error analysis in manufacturing systems. Notably, he served as Director of the Institute of Metrology and Biomedical Engineering (2012–2020) and later as Dean of the Faculty of Mechatronics (2020). He received the Polish Prime Minister’s Prize for Scientific Achievements (2012) and multiple scholarships from the Foundation for Polish Science. Education: PhD (2002), D.Sc. (2011), Warsaw University of Technology; Visiting Professor at École Polytechnique de Montréal (2005–2006). Research interests include coordinate measuring machine (CMM) performance, probing system accuracy, and industrial CT applications. His work addresses dynamic error identification, probe error compensation, and precision measurement techniques. Recent projects involve high-density point cloud correction, scanning probe validation, and pediatric growth measurement systems. His articles analyze topics like probe reliability, CNC machine tool errors, and X-ray CT threshold optimization. Awards also include recognition for leadership in standardization bodies, including roles in Poland’s Council for Metrology and Standardization. He has supervised 6 PhD students and numerous master’s candidates, contributing to over a dozen funded research projects. His lab, the Virtual Manufacturing Research Laboratory, integrates metrology, mechatronics, and biomedical engineering for advanced measurement solutions.
Prof. Mariusz Deja serves as the Dean of the Faculty of Mechanical Engineering and Ship Technology at Gdańsk University of Technology. He holds a PhD (2001) and habilitation (2014) in Mechanical Engineering. His academic roles include Head of the Department of Manufacturing and Production Engineering (since 2019), and former Vice-Dean for Education (2016–2020) and Vice-Dean for Cooperation (2020–2024). Education: Master's in Mechanical Engineering (1993), Pedagogical Studies (1993), and postgraduate courses in TQM and ECO-Integrated Mechanical Engineering (1997). Professional experience includes roles as an assistant (1993–2001), assistant professor (2002–2017), associate professor (2017–2019), and full professor (since 2019). Research focuses on abrasive machining, additive manufacturing, and CAPP algorithms. Key interests include material removal processes, precision engineering, and tool fabrication using AM. Collaborations include visiting professorships at China's Dezhou University (2018), Germany's Technical University of Berlin (2021–present), and Sweden's KTH Stockholm (2023–2024). Awards include the Silver Cross of Merit (2016) and multiple Rector Awards for scientific, didactic, and organizational achievements. His work spans over 98 publications, with recent studies on 3D printing applications, container terminal logistics, and AI-driven defect analysis. Labs/Teams: Involved in research infrastructure related to additive manufacturing tools and precision machining systems. Active in projects like the NEPTUN initiative (Horizon Europe-funded) and Industry 4.0 collaborations.
Caglar Oskay is an Associate Professor in the Department of Civil and Environmental Engineering at Vanderbilt University, where he has held academic positions since 2006. He specializes in multiscale computational mechanics, materials modeling, and failure analysis of heterogeneous materials. His research integrates advanced numerical methods such as the Extended Finite Element Method (XFEM), reduced-order homogenization, and variational multiscale enrichment to study composite materials, viscoelastic systems, and polycrystalline structures under extreme conditions. Dr. Oskay has been recognized with awards including the Chancellor Faculty Fellow (2016–2018) and ASCE ExCEEd Fellow (2011). Education: PhD (Civil Engineering, Rensselaer Polytechnic Institute, 2003), M.S. (Civil Engineering, Rensselaer Polytechnic Institute, 2000), M.S. (Applied Mathematics, Rensselaer Polytechnic Institute, 2000), B.S. (Civil Engineering, Middle East Technical University, 1998). Research focuses on predictive computational models for material behavior under mechanical, thermal, and chemical loading. Key areas include fatigue life prediction, damage accumulation in composites, and coupled transport-deformation phenomena. Recent work addresses multiscale modeling of nickel-based superalloys, polyurea-coated composites, and energetic materials under dynamic loading. His contributions span 100+ peer-reviewed publications, including seminal studies in International Journal for Multiscale Computational Engineering and Acta Materialia . His articles emphasize multiscale frameworks for heterogeneous materials, with trends in reduced-order methods, uncertainty quantification, and interdisciplinary applications (e.g., biology, energy systems). Awards highlight his educational and technical leadership. Advising and grants include collaborative projects on composite durability and energetic material simulation. Dr. Oskay leads the Multiscale Computational Mechanics Lab (MCML), advancing computational tools for engineering materials research.
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.
Dr. Kamil Waldemar Lemanek is a Polish-American academic affiliated with Maria Curie-Skłodowska University as an Assistant Professor in the Department of Logic and Cognitive Science under the Faculty of Philosophy and Sociology. He also holds an adjunct position at the University of Warsaw Institute of Philosophy. His scholarly focus bridges philosophy of language , philosophy of mind , and ontology , with significant contributions to inferentialism, semantic theory, and pedagogical innovation. PhD in Philosophy (2023), University of Warsaw Research on natural language architecture, delusion frameworks, and educational technology Extensive editorial collaboration and grant acquisition His publications reveal a thematic interplay between linguistic finitism , semantic atomism , and social epistemology . Notably, he explores unconventional pedagogical tools like ancient astronaut theory for teaching informal logic. Though no specific scientific awards are listed, his national/international grants (e.g., NCN grant for research on language architecture) demonstrate institutional support. Teaching innovations include AI-assisted peer review simulations in academic writing instruction.
Piotr Koniorczyk is a full professor at the Military University of Technology, specializing in mechanical engineering and thermal sciences. His research focuses on thermophysical properties of materials, heat transfer in engineering systems, and advanced materials for aerospace and defense applications. He has published over 91 articles and supervised 12 promoted theses, demonstrating expertise in topics such as thermal analysis of metals, composite materials, and thermal management systems. His work includes studies on steel barrel heat transfer in firearms, thermophysical properties of tool steels, and passive cooling solutions for high-power electronics. Notable projects involve numerical simulations of heat transfer in rocket engines and gun barrels, as well as investigations into phase-change materials for thermal energy storage. His research has contributed to advancements in materials science, thermal engineering, and aerospace technology.
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.
Jakub Grela is a Lecturer at AGH University of Science and Technology, affiliated with the Department of Power Electronics and Automation of Energy Conversion Systems within the Faculty of Electrical Engineering, Automatics, Computer Science, and Biomedical Engineering. His work focuses on building automation systems, IoT applications in energy management, and renewable energy integration. Current faculty member at AGH University Specializes in energy efficiency and smart grid technologies Active in IoT-driven building automation research Research interests include hybrid energy storage systems, thermal modeling for heating optimization, and demand response solutions in smart grids. His publications emphasize practical implementations of IoT in consumer electronics and energy management systems. His recent work explores trends in transactive energy systems, human-centric building automation, and heat recovery simulations. Articles highlight case studies across university infrastructure, street lighting, and residential energy systems, demonstrating cross-disciplinary applications of IoT in energy efficiency.
Szymon Płotka is a Researcher in the Medical Imaging and Robotics department at the University of Amsterdam's Informatics Institute. His work focuses on advancing prenatal care through deep learning, particularly in fetal ultrasound analysis and AI-driven medical solutions. He holds a PhD in Computer Science from the University of Amsterdam (2024), with a thesis on enhancing prenatal care via machine learning. Research Interests : Integration of deep learning techniques for medical image analysis Development of AI tools for diagnostic accuracy and clinical workflow optimization Multimodal data fusion in healthcare Real-time surgical imaging applications Recent work emphasizes fetal biometry measurements, endoscopic synthetic datasets, and real-time placental vessel segmentation. His research bridges cutting-edge AI with clinical practice, aiming to improve accessibility and efficiency in medical imaging. Key Contributions : Advances in fetal ultrasound video analysis matching human expert accuracy Pioneering synthetic endoscopic dataset generation with diffusion models Development of BabyNet++ for birth weight prediction No formal students listed, but his projects likely involve collaborations with academic teams. Active in organizing and participating in medical imaging challenges (e.g., FeTA, FetReg).
Dr hab. Michał Wyrostkiewicz, professor at the John Paul II Catholic University of Lublin (KUL), chairs the Department of the History of Liturgy and is a leading voice in moral theology, liturgical studies, ecological ethics, and media ethics. His interdisciplinary research bridges theology, communication, and environmental studies, supported by numerous national and international grants. Education and Affiliations: Doctor habilitatus (dr hab.) in theology, awarded the academic title of professor by the President of Poland (prof. KUL) Faculty member, John Paul II Catholic University of Lublin (permanent post) Member of the Polish Society for Social Communication and Catholic Theological Ethics in the World Church Research Interests: Michał Wyrostkiewicz’s scholarly work focuses on moral and liturgical theology , with a particular emphasis on ecological responsibility rooted in Catholic social teaching. He explores infoethics —ethical use of information and media—examining how digital technologies shape human identity and community. His recent projects investigate artificial intelligence in pastoral care and the theological implications of the Anthropocene , seeking to integrate environmental stewardship, truthful communication, and liturgical spirituality. Publications Trends: Across the last decade his publications cluster in four dominant areas: (1) ecological theology and ethics (ecology of the Mass, circular economy, eco-virtues); (2) media and infoethics (disinformation, Catholic influencers, digital morality); (3) pastoral-liturgical studies (renewal of liturgy, catechesis, sacramental practice); and (4) moral anthropology (corruption, lying, forgiveness, human dignity). This body of work combines rigorous theological argument with empirical studies and educational tool development. Scientific Awards & Distinctions: Medal of the National Education Commission – Polish state decoration for outstanding contributions to education Long-Service Medal – awarded by the Polish state for dedicated academic service Rector of KUL Individual Award – annual recognition for exceptional research performance Rector of KUL Team Award – shared prize for collaborative research excellence Pro-Rector Award for the Best Scored Publication 2023 – university distinction for highest-impact scholarly output Research Leadership & Doctoral Supervision: Professor Wyrostkiewicz has been principal investigator on over a dozen funded projects financed by the Polish National Science Centre, Ministry of Science and Higher Education, KUL internal budget, and EU programmes such as Horizon 2020 and Erasmus+. Representative grants include “Human Ecology 2.0” , “Theology in the Age of Artificial Intelligence” , and “Town & Gown 2.0” (strategic university-city cooperation in V4+Ukraine). He currently supervises multiple PhD dissertations in moral theology, liturgical studies, and media ethics, and has served as reviewer or opponent in numerous habilitation and professorial nomination procedures. Laboratories & Collaborative Networks: He coordinates an informal Research Group on Eco-Theology and Infoethics within KUL, bringing together theologians, environmental scientists, and communication scholars. The group maintains active partnerships with the Pontifical Universities in Rome (Santa Croce, Angelicum, Lateranense), University of Oxford (Bodleian Libraries), University of Prešov (Slovakia), and a network of Catholic universities across Central and Eastern Europe. These collaborations facilitate joint conferences, visiting scholar exchanges, and comparative empirical studies on ecological awareness and media practice among theology students.
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.
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.
Szymon Cygan, PhD, is an Assistant Professor and Deputy Dean for Students Affairs and Promotion at the Institute of Metrology and Biomedical Engineering , part of the Faculty of Mechatronics at Warsaw University of Technology. His work focuses on strain imaging methods for echocardiography, ultrasonic imaging, and biomedical engineering applications. Education: M.Sc. (2003) in Automatics and Robotics with Biocybernetics and Biomedical Engineering specialization; Ph.D. (2011) on displacements and strain estimation for ultrasonic strain imaging. Research: Specializes in speckle tracking echocardiography, left ventricular phantom modeling, finite element simulations, and validation of strain estimation algorithms using synthetic and physical models. Awards: No specific scientific awards explicitly mentioned. Projects: Involved in 2 projects, including development of low-cost gait analysis systems and synthetic cardiac phantom validation. Labs: Part of Krzysztof Kaluzynski's Lab, focusing on biomedical engineering and cardiac imaging.
