Bydgoszcz University of Science and TechnologyPoland
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.
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.
Bydgoszcz University of Science and TechnologyPoland
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.
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.
Professor Tomasz Kapitaniak is a distinguished academic in the field of nonlinear dynamics and theoretical mechanics. He serves as a Professor of Theoretical and Applied Mechanics and Head of the Division of Dynamics at the Faculty of Mechanical Engineering, Technical University of Lodz, Poland. His career spans over three decades at the university, where he has made significant contributions to the understanding of nonlinear systems, chaos theory, and mechanical oscillations. Professor Kapitaniak holds advanced degrees in both mechanics and applied mathematics from the Technical University of Lodz and the University of Lodz. His educational background includes: M.Sc. in mechanics, Faculty of Mechanical Engineering, Technical University of Lodz (1982) M.Sc. in applied mathematics, Faculty of Mathematics, Physics and Chemistry, University of Lodz (1985) Ph.D. in mechanics, Faculty of Mechanical Engineering, Technical University of Lodz (1985) D.Sc. in mechanics, Faculty of Mechanical Engineering, Technical University of Lodz (1988) Professor of technical science, title given by the President of Poland (1995) His research focuses on nonlinear dynamics, with particular emphasis on mechanical oscillations, stability, bifurcations and chaos, stochastic dynamics, and applications of nonlinear dynamics in mechanical engineering. Professor Kapitaniak is renowned for his work on the development of methods for controlling chaos without feedback, identification of new types of bifurcations, synchronization mechanisms in coupled mechanical oscillators, and explaining the origin of randomness in mechanical systems. His research has evolved from fundamental theoretical work to increasingly applied studies involving complex networks, biological systems, and engineering applications. Professor Kapitaniak has published over 300 scientific papers in renowned journals, cited over 8,000 times. His work exhibits a consistent focus on understanding complex nonlinear phenomena across various physical systems. The trend in his recent publications shows continued exploration of synchronization phenomena, extreme events in dynamical systems, and applications of nonlinear dynamics to biological, mechanical, and physical systems. His most recent work demonstrates a growing interest in multistability, chimera states, and the prediction of tipping phenomena in complex systems. Among his notable scientific achievements and distinctions are: Election as a member of the Polish Academy of Sciences (corresponding member in 2013, ordinary member in 2019) Election to Academia Europaea in 2021 Honorary doctorates from Saratov State University (Russia, 2001) and Lublin University of Technology (Poland, 2014) Multiple prestigious fellowships including the British Council Fellowship (1989), King Abdul Aziz Award Fellowship (1990), and Fulbright Fellowship (1997) Editorial roles including Associate editor of Chaos, Solitons and Fractals since 1990 and member of editorial boards of several other prestigious journals Throughout his career, Professor Kapitaniak has been actively involved in mentoring the next generation of researchers, having supervised numerous PhD students including Jerzy Wojewoda, Anton van Wyk, Barbara Błażejczyk-Okolewska, Andrzej Stefański, Andrzej Kozłowski, and Przemysław Szumiński. He has secured significant research funding from various national and international sources including the Ministry of Science and Higher Education (Poland), Deutscher Akademischer Austauschdienst, The Royal Society of London, and others. His research team has maintained strong international collaborations with institutions worldwide, including universities in the United States, United Kingdom, Germany, Brazil, Russia, and Ukraine. He leads the Division of Dynamics at the Technical University of Lodz, which serves as a hub for research in nonlinear dynamics, mechanical oscillations, and related fields. The division maintains strong international collaborations with institutions worldwide and continues to produce cutting-edge research in the field of nonlinear dynamics and its applications.
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.
Dorota Piekarczyk is a full Professor at the University of Marie Curie-Skłodowska (UMCS) in Lublin, Poland, affiliated with the Faculty of Languages, Literatures and Cultures. She has served since 2002 and held the position of Deputy Director at the Institute of Polish Philology from 2013-2019. Her research focuses on the intersections of language and cognition, particularly through semantic analysis , pragmatic frameworks , and linguistic worldview studies. She specializes in paratextual elements of publications, examining how covers, blurbs, and series information shape reader expectations and societal knowledge reception. The 2020 monograph on book covers represents her most comprehensive work on paratextual analysis. Her recent publications (2020-2019) investigate paratextual persuasion techniques popular culture integration in science communication publisher-reader dynamics while maintaining long-term contributions to floral categorization studies and cognitive schemata in texts. Scientific achievements include 2014 Prime Minister's Award for 'Metafory metatekstowe' ORCID: 0000-0002-8859-7897 648 total ministerial points across 12 publications
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.
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.
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.
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.
Dr. hab. Magdalena Skurzok is an Associate Professor at Jagiellonian University in Krakow, Poland, affiliated with the Faculty of Physics, Astronomy and Applied Computer Science. She conducts research in nuclear physics with a focus on exotic nuclear matter, particularly mesic nuclei and mesonic atoms. Her work bridges fundamental particle physics with practical medical applications through advanced detector systems including the J-PET scanner and SIDDHARTA-2 apparatus. Her educational background includes: Habilitation thesis: "Investigation of exotic nuclear matter in the form of mesic nuclei and mesonic atoms" (2024) Doctoral thesis: "Search for eta-mesic helium via dd -> 3Henpi0 reaction by means of the WASA-at-COSY facility" (2016) Diploma thesis: "Feasibility study of eta-mesic nuclei production by means of the WASA-at-COSY and COSY-TOF facilities" (2010) Dr. Skurzok's research primarily focuses on nuclear physics, particularly the investigation of exotic nuclear matter in the form of mesic nuclei and mesonic atoms. Her work explores the bound states of the eta meson with light atomic nuclei and kaon atoms, contributing to our understanding of strong interactions in nuclear systems. She is also involved in PET tomography research, developing novel imaging techniques with applications in medical diagnostics. Her experimental work utilizes advanced detector systems including the J-PET scanner and the SIDDHARTA-2 apparatus at the DAFNE collider. Analysis of Dr. Skurzok's recent publications reveals a strong focus on kaonic atoms research, precision X-ray spectroscopy, and PET imaging technology development. Her work bridges fundamental nuclear physics with practical medical applications, particularly in brain imaging and cancer diagnostics. The interdisciplinary nature of her research connects particle physics, nuclear spectroscopy, and medical imaging technologies. Dr. Skurzok is actively involved in several major research collaborations: SIDDHARTA-2 experiment at DAFNE collider for kaonic atoms research J-PET collaboration developing novel PET imaging technology AMADEUS experiment investigating low-energy K- interactions with nuclei WASA-at-COSY facility for mesic nuclei research Her laboratory work primarily involves the SIDDHARTA-2 apparatus for X-ray spectroscopy of kaonic atoms and the J-PET scanner for positron emission tomography. These advanced detector systems enable precision measurements of exotic nuclear phenomena and innovative medical imaging applications. Dr. Skurzok's research group collaborates extensively with international institutions including CERN, GSI, and various European research centers.
Wrocław University of Science and TechnologyPoland
Daniel Bejmert, PhD is an academic researcher at the Department of Electrical Power Engineering, Faculty of Electrical Engineering, Wrocław University of Science and Technology. His work focuses on power system protection with advanced signal processing and artificial intelligence techniques. Institution: Wrocław University of Science and Technology Faculty: Faculty of Electrical Engineering Department: Electrical Power Engineering Email: daniel.bejmert@pwr.edu.pl Research interests include: Analog and digital signal processing in power systems Multicriterial adaptive protection systems Digital simulation of transient phenomena Artificial intelligence applications for protection algorithms His publications demonstrate expertise in: Power system protection and control Transformer differential protection Islanding detection techniques Current transformer saturation analysis Frequency stabilization methods Neural network applications in power systems Contact details: Office: Building D-20, Room 418 Phone: +48 71 3493 Address: Janiszewskiego 8, 50-372 Wrocław
Wrocław University of Science and TechnologyPoland
Marek Zaradny is a researcher affiliated with the Faculty of Information and Communication Technology at Wrocław University of Science and Technology, specifically within the Department of Telecommunications and Teleinformatics . His work focuses on microwave filter design, RF circuit synthesis, and signal processing. Research Interests : Microwave Engineering RF Filter Design Signal Processing Telecommunications Systems His recent publications explore advanced methodologies for bandpass filter synthesis, immittance transformations, and distributed network realizations. These contributions highlight his expertise in optimizing microwave circuits for improved performance and attenuation characteristics. Professional Affiliations : Wrocław University of Science and Technology Department of Telecommunications and Teleinformatics
