Andrzej Majkowski is an Associate Professor at the Institute of the Theory of Electrical Engineering, Measurement and Information Systems, Faculty of Electrical Engineering, Warsaw University of Technology. His career spans over two decades of research in biomedical engineering, focusing on brain-computer interfaces, signal processing, and emotion recognition. Active in both teaching and research, he contributes to advancing methodologies in electrophysiological signal analysis. Warsaw University of Technology Institute of the Theory of Electrical Engineering, Measurement and Information Systems Faculty of Electrical Engineering Specializing in biomedical engineering , Majkowski's research bridges control systems and information technologies with neuroscience applications. His work explores brain-computer interfaces , EEG/EMG signal processing , and emotion recognition using multimodal physiological data. Recent studies focus on deep learning architectures for artifact removal and classification tasks. Recent publications highlight trends in CNN-LSTM hybrid models for signal denoising, convolutional networks for seizure detection, and machine learning applications in visual evoked potential analysis. His work spans both clinical applications (epilepsy monitoring) and human-computer interaction (emotion recognition, sign language detection). With over 98 documented publications and significant bibliometric indicators (h-index 13 in Scopus), Majkowski has supervised 95 promoted theses. His research includes one funded project and collaborations in biomedical instrumentation, though specific award details remain unspecified in available records.
Maciej Zięba is an academic researcher affiliated with the Faculty of Information and Communication Technology at Wrocław University of Science and Technology, specifically within the Department of Artificial Intelligence . His work spans machine learning, deep learning, and computer vision, with a focus on hyperspectral imaging, autonomous systems, and 3D modeling. Recent research includes uncertainty-aware sensor deployment for autonomous vehicles, low-light image enhancement algorithms, and probabilistic regression frameworks for tabular data. He has co-authored publications on flow-based models, hypernetworks, and neural radiance fields (NeRF) applied to 3D face rendering. Contact: maciej.zieba@pwr.edu.pl
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.
Damian Grela is a Lecturer in the Department of Automation and Computer Science at the Faculty of Electrical and Computer Engineering, Cracow University of Technology. His work spans two distinct research domains: software engineering (focusing on BPEL processes, web services, and fault injection testing) and environmental engineering (specializing in diatomite-based biogennic pollutant removal, rain gardens, and surface water quality monitoring).
Roman Matuszewski is a retired Associate Professor at the University of Bialystok, affiliated with the Faculty of Philology's Department of Applied Linguistics. His research focuses on automated reasoning, formalized mathematics, and the Mizar Project, which he has been involved with since its inception in 1973. He holds a PhD in Computer Science from Shinshu University (2000) and has held academic positions at multiple institutions, including part-time roles at Bogdan Janski University. Education: PhD in Computer Science (2000), Master of Science in Mechanics (1975), Engineer (1973), all from Polish institutions. His work emphasizes formal proof systems, mathematical knowledge management, and education integration of automated reasoning tools. Research interests include automated deduction, formal proof verification, and the application of these methods to mathematics education. His contributions to the Mizar Mathematical Library and its 50-year history (celebrated in 2023) are foundational for interactive theorem proving. Key awards include the Silver Cross of Merit (2004) and multiple Rector’s prizes. He has organized major conferences like MKM2004 and served on program committees for events such as IJCAR and Tableaux. Grants include leadership roles in EU-funded projects like TYPES and CALCULEMUS. His work bridges computer science and mathematics through formalized systems, impacting both research and education.
Prof. Wojciech Sobieski is a faculty member at the Department of Mechanics and Fundamentals of Machine Design within the Faculty of Technical Sciences at the University of Warmia and Mazury in Olsztyn . His research focuses on fluid mechanics, numerical modeling, and porous media analysis, with applications in environmental engineering, hydraulic systems, and 3D printing. Academic Rank: Professor Scientific Discipline: Mechanical Engineering Key Research Areas: Tortuosity Analysis, Multiphase Flow, DEM Simulations His recent publications highlight advancements in computational methods for granular porous media, fluid flow modeling, and thermodynamic applications. Notable trends include the use of the Waterfall Algorithm for geometric analysis and sensitivity studies of numerical models like the Eulerian multiphase approach. He has contributed to understanding Forchheimer's laws and cavitation phenomena in hydraulic systems. Prof. Sobieski oversees the PathFinder Project , a research initiative focused on numerical modeling of porous media. His laboratory maintains infrastructure for multiphase flow simulations and particle-scale modeling. He has supervised 2 doctoral students to completion but currently has no active advisees.
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.
Konrad Kowalczyk is an Associate Professor at AGH University of Science and Technology in Krakow, Poland, where he heads the Signal Processing Group within the Faculty of Computer Science, Electronics and Telecommunications. With extensive international experience from institutions including Queen's University Belfast, Stanford University, and Fraunhofer Institute, he has established himself as a leading researcher in audio and speech signal processing. His academic journey includes B.Eng. and M.Sc. degrees from AGH University (2005), a Ph.D. from Queen's University Belfast (2009), and a Habilitation in ICT from AGH University (2020). B.Eng. and M.Sc. in Electronics and Telecommunications, AGH University of Krakow (2005) Ph.D. in Electronics, Queen's University Belfast, UK (2009) Habilitation (D.Sc.) in Information and Communication Technology, AGH University of Krakow (2020) Kowalczyk's research spans multiple cutting-edge areas in audio processing, with particular focus on speech and audio signal processing enhanced by machine learning techniques. His work integrates deep neural networks with traditional signal processing methods to address challenges in array signal processing , speech enhancement , and speaker recognition . The research group he leads explores innovative applications in distributed signal processing for IoT , acoustic event detection , and spatial audio rendering , bridging theoretical advances with practical implementations. His recent publications demonstrate a clear trend toward integrating deep learning with traditional signal processing techniques, particularly in speaker diarization, source separation, and robust speech recognition. The research increasingly focuses on real-world applications requiring reverberation-robust processing , distributed microphone array systems , and end-to-end neural architectures that can operate in challenging acoustic environments. There's a noticeable shift toward more complex, integrated systems that combine multiple signal processing tasks. Stanislaw Staszic Medal for best graduate of AGH (2005) IEEE Best Student Paper Contest finalist (2007) AES Student Technical Paper Award winner (2008) Best Student Paper Award at IWAENC conference (2014) Best Paper Awards at IEEE SPA conferences (2016, 2019) Polish Ministry of Science Scholarship for Distinguished Young Scientists (2016-2019) Prime Minister Award for outstanding scientific achievements (2020) As Principal Investigator, Kowalczyk leads multiple significant research projects including "Acoustic Intelligence" (2024-2028) funded by National Science Center, and "Deep extraction for robust speech recognition" (2023-2028). He has successfully secured funding from prestigious programs including First TEAM from the Foundation for Polish Science, and EU FP7 projects. His research group actively supervises Ph.D., M.Sc., and B.Eng. students, with strong connections to international institutions including Aalto University and IEEE Signal Processing Society. The research output includes numerous journal publications, conference papers, patents, and software implementations that have advanced the field of audio signal processing. Kowalczyk leads the Signal Processing Group at AGH University, which focuses on developing innovative solutions for speech and audio processing challenges. The group maintains strong collaborations with international institutions including Aalto University (Finland), and participates in European research initiatives. Their work spans theoretical development through practical implementation, with applications ranging from medical voice assistants to distributed acoustic sensor networks.
Summary Adam Szymkiewicz is a full Professor and Vice-Dean for Scientific Research at the Faculty of Civil and Environmental Engineering, Gdańsk University of Technology. He leads the Department of Geotechnics and Water Engineering and holds academic positions since 2021. His research focuses on groundwater flow, contaminant transport, and numerical modeling in porous media. Key roles include Head of Department (2022–present) and Vice-Dean (2024–present). Education includes a PhD from Joseph Fourier University (2004) and habilitation from Gdańsk University of Technology (2013). Research Interests: Hydraulic properties of porous media, multiphase fluid flow, climate change impacts, and integrated hydrological modeling. Notable projects include AQUIGROW (HORIZON EUROPE) and SOILPROM. Publications: Over 50 peer-reviewed articles on topics like PFAS migration, groundwater recharge, and MODFLOW coupling. Recent work emphasizes climate change effects on aquifers and coastal hydrogeology. Awards: Multiple Rector awards (2012–2022) and Polish Academy of Sciences Award (2013). Membership: AGU, EGU, InterPore, and Polish Hydrogeologists Society. Editorial roles include Associate Editor of Acta Geophysica .
Paweł Pilarczyk is an Associate Professor at the Institute of Applied Mathematics within the Faculty of Applied Physics and Mathematics at Gdańsk University of Technology, where he has been employed since 2018. His research spans multiple mathematical disciplines with applications across various scientific fields. Dr. Pilarczyk's research interests include dynamical systems , computational topology , rigorous numerics , and applications of advanced computational techniques . His work bridges theoretical mathematics with practical applications in neuroscience, cardiology, ecology, and epidemiology. Analyzing his publication record from 2025 back to 2007 reveals a consistent focus on rigorous mathematical approaches to understanding complex systems. His recent work shows increasing interdisciplinary applications, particularly in medical diagnostics (sleep apnea detection, heart rate variability analysis) and neuroscience (neuron modeling), while maintaining strong foundations in pure dynamical systems theory. As project manager for the OPUS-funded "Topological and numerical methods in dynamical systems" (since 2022), he leads significant research initiatives at the Department of Differential Equations and Mathematical Applications. Dr. Pilarczyk maintains an active research program with collaborators across multiple institutions, evidenced by his extensive publication record and research data sets available through Gdańsk Tech's Bridge of Knowledge platform.
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.
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.
