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.
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.
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.
Monika Rosińska is an Assistant Professor at SWPS University's Faculty of Design in Warsaw, where she serves as Head of the Department of Design Theory and Research and as Dean's Representative for Interdisciplinarity. She is affiliated with both the Institute of Social Sciences and the Design Institute within the university. Her research focuses on the socio-cultural dimensions of design practices, with particular expertise in non-anthropocentric design, science and technology studies (STS), and critical/speculative design approaches. She investigates the history of design within political, social and cultural contexts, and examines the sociology of objects in everyday life. Dr. Rosińska explores why the creative process extends beyond form and function, pursues definitions of "good design," and investigates what matters to contemporary designers. Her scholarly work reveals consistent themes across publications, with recent research increasingly focused on multi-species communities and non-anthropocentric approaches to design. Her 2019 paper "Zoepolis: Non-anthropocentric design as an experiment in multi-species care" represents a significant contribution to this emerging field, building on earlier work exploring urban revitalization and participatory design. Dr. Rosińska has curated exhibitions including "Zoepolis. Design for Plants and Animals," which serves as both research output and practical exploration of her theoretical frameworks. Her publications span from foundational works on collective behaviors ("Deindywiduacja. Socjologia zachowań zbiorowych") to cutting-edge explorations of AI in visual arts (2025). She actively contributes to academic discourse through platforms including Google Scholar, ResearchGate, Academia.edu, and ORCID, maintaining visibility across multiple scholarly networks. Her work bridges sociology and design in innovative ways that challenge traditional disciplinary boundaries.
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.
Professor Daniel Gryko leads a prominent research group at the Institute of Organic Chemistry, Polish Academy of Sciences, specializing in advanced functional dyes and photochemistry. His work bridges fundamental organic synthesis with practical applications in bioimaging, molecular electronics, and nanomaterials. With over 150 publications and numerous high-impact grants, including an ERC Advanced Grant and multiple Horizon Europe projects, Gryko has established himself as a leader in the field of novel chromophore design. Gryko's research focuses on developing innovative fluorescent dyes with exceptional photophysical properties, particularly exploring fluorescence of nitroaromatics, two-photon absorption phenomena, and excited-state intramolecular proton transfer (ESIPT). His group specializes in several key structural platforms including corroles, diketopyrrolopyrroles, pyrrolo[3,2-b]pyrroles, dipyrrolonaphthyridinediones, porphyrins, and coumarins. Recent work has centered on creating strongly emitting helicenes, quadrupolar dyes with unique symmetry-breaking properties, and developing specialized fluorophores for super-resolution microscopy applications. Analysis of Gryko's recent publications reveals a strong emphasis on molecular design strategies for controlling photophysical behavior. His group frequently employs π-expansion techniques, heteroatom doping, and strategic substitution patterns to tune emission properties. A significant portion of their work focuses on overcoming traditional limitations in fluorophore design, such as the non-fluorescence of nitroaromatics, through innovative molecular architectures. Gryko has received prestigious recognition including an ERC Advanced Grant for the ARCHIMEDES project targeting NIR-II emission efficiency, multiple Horizon Europe grants, and the TEAM grant from the Foundation for Polish Science supporting development of fluorescent probes for super-resolution microscopy. His group's work has resulted in numerous publications in top-tier journals including Journal of the American Chemical Society , Chemical Science , and Angewandte Chemie . Professor Gryko actively mentors a diverse research team including PhD students, postdoctoral researchers, and collaborators worldwide. His group has secured substantial funding including Horizon Europe grants for PhotoBrane and APACE projects, ERC funding, and multiple Polish National Science Centre grants. Current projects focus on developing novel fluorescent probes for super-resolution microscopy, creating bio-mimetic sunlight-pumped lasers, and designing photo-switchable membranes for molecular separation. The Gryko group operates a well-equipped laboratory focused on organic synthesis and photophysical characterization. Their work spans from fundamental molecular design to practical applications in bioimaging and materials science. Recent expansions of their research program include development of probes for detecting SARS-CoV-2 proteases, demonstrating the group's ability to pivot toward addressing pressing societal challenges.
Dr. Magdalena Ślusarz serves as an Adjunct Professor in the Department of Theoretical Chemistry at the Faculty of Chemistry, University of Gdańsk. Her research focuses on computational approaches to structural biology problems, particularly in viral immunomodulation and receptor-ligand interactions. Her research interests span computational chemistry , molecular modeling of protein structures , and structural analysis of viral immune evasion mechanisms . She specializes in applying molecular dynamics simulations, NMR spectroscopy data interpretation, and UNRES force field methodologies to study herpesvirus proteins (particularly UL49.5), opioid receptor interactions, and vasopressin receptor systems. Her work bridges theoretical chemistry with biomedical applications including viral pathogenesis and neuropharmacology. Analysis of her recent publications reveals a strong focus on herpesvirus immunomodulation mechanisms (2023-2024), particularly how viral proteins hijack cellular degradation pathways. Earlier work demonstrates expertise in computational structural biology methodologies including UNRES force field development for membrane proteins (2019) and protein structure prediction (2016-2020). Her research consistently applies molecular modeling to solve biomedical problems ranging from viral immune evasion to neuropharmacology. Dr. Ślusarz maintains active research in the Laboratory of Molecular Modeling at the University of Gdańsk, where she applies computational approaches to protein structure-function relationships. Her work involves collaborations across international research teams, particularly evident in large-scale projects like the WeFold consortium for protein structure prediction.
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.
Daria Hemmerling , PhD, Eng., is a Lecturer at the Department of Metrology and Electronics under the Faculty of Electrical Engineering, Automatics, Computer Science and Biomedical Engineering at AGH University of Science and Technology in Kraków. Her research focuses on the intersection of biomedical engineering, voice analysis, and artificial intelligence, particularly for neurological and cardiovascular disease diagnostics. Research Interests : Applying mixed reality and AI for Parkinson’s disease assessment Voice/speech biomarkers for heart failure and neurodegenerative disorders Deep learning techniques in medical imaging (e.g., skull segmentation/reconstruction) Haptic feedback systems for multisensory interaction Simulation training in electrophysiology education Unsupervised learning and modality translation in biomedical signal processing Scientific Trends : Her recent work emphasizes multimodal diagnostic systems integrating voice analysis, VR/MR visualization, and deep learning. She explores explainable AI for medical classification tasks, data augmentation strategies, and innovative haptic/gamification interfaces.
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.
Robert Sitnik is a Professor and Dean of the Faculty of Mechatronics at Warsaw University of Technology, where he is affiliated with The Institute of Micromechanics and Photonics. He earned his Doctorate in 2002 and has established himself as a leading researcher in 3D optical measurement techniques and applications. His research focuses on 3D light measurement, optical shape analysis, structured light techniques, and 3D data processing with applications spanning cultural heritage documentation and medical imaging. As the leader of the 3D/4D Optical Surface Measurement Team, he has pioneered innovative approaches to surface measurement and documentation. His work demonstrates strong interdisciplinary connections between mechanical engineering, computer vision, and practical applications in both cultural preservation and healthcare. His research has led to significant advancements in 3D scanning technologies, particularly for human body analysis and cultural heritage conservation. His publications reveal a consistent research trajectory focused on improving accuracy, efficiency, and applicability of 3D measurement systems. His scientific impact is evidenced by 159 publications, an h-index of 18 in Scopus and 17 in Web of Science, and 103 promoted theses. His research has been supported by 22 projects, resulting in 1 patent and substantial contributions to both academic knowledge and practical applications. As an academic leader, he has supervised numerous students and researchers, contributing significantly to the development of expertise in optical measurement technologies. His work bridges theoretical research with real-world applications in medical diagnostics, cultural heritage preservation, and industrial measurement systems.
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.
