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Mariusz DejaView profile

Professor

• Additive Manufacturing
• Computer-Aided Manufacturing (CAM)
• Abrasive Machining
• +3 more

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.

• Computer Vision
• Robotics
• Human-Computer Interaction
• +4 more

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 GrzybowskiView profile

Adjunct Professor

• Artificial Intelligence in Chemistry
• Computer-Assisted Organic Synthesis
• Reaction Network Analysis
• +3 more

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.

• Biomedical Engineering
• Voice Analysis
• Artificial Intelligence
• +5 more

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.

• Signal Processing
• Electronics
• Biomedical Engineering
• +5 more

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.

Daniel BejmertView profile

Researcher

• Analog and Digital Signal Processing
• Multicriterial and Adaptive Systems for Power System Protection
• Digital Simulation of Transient Phenomena in Power Systems
• +1 more

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

Jan MajkutewiczView profile

Lecturer

• Natural Language Processing
• Machine Learning
• Knowledge Representation
• +3 more

Jan Majkutewicz serves as an Assistant lecturer at the Department of Computer Systems Architecture within the Faculty of Electronics, Telecommunications and Informatics at Gdańsk University of Technology. His academic position focuses on advancing computational methodologies in natural language processing and knowledge representation systems. His research spans Natural Language Processing, Machine Learning, and Knowledge Representation with specific expertise in Large Language Models and graph-based embeddings. Current work investigates human-AI alignment through historical text analysis and neural representations of semantic hierarchies. Methodological innovations include cost-effective preference dataset generation and category graph embedding techniques that preserve structural relationships in knowledge bases. Publication analysis reveals consistent specialization in NLP and knowledge representation. The 2025 EditPrefs framework leverages historical text edits to address dataset scarcity in preference learning, while the 2021 Wikipedia category embedding research demonstrates practical applications for taxonomy navigation and parent category prediction through neural graph representations.

Somnath GhoshView profile

Professor

• Computational Mechanics
• Multiscale Modeling
• Integrated Computational Materials Engineering (ICME)
• +6 more

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.

Ahmed Abdeen HamedView profile

Assistant Professor

• Drug Repurposing
• Network Analysis
• Artificial Intelligence in Healthcare
• +6 more

Dr. Ahmed Abdeen Hamed is a former Assistant Professor of Data Science and Artificial Intelligence at Norwich University and a former Research Team Leader in Clinical Data Science. He holds a Ph.D. from the University of Vermont (2014) and has extensive industry experience in pharmaceutical research. His work focuses on computational methods for drug discovery, network analysis, and AI-driven healthcare solutions, particularly in drug repurposing for diseases like COVID-19. He has developed algorithms such as MolecRank and NeoNet, and holds a patent for specificity-based molecule ranking systems. Education: PhD in Data Science (University of Vermont, 2014). Research Interests: Network-based drug discovery, biomedical informatics, AI in healthcare, clinical data science, and combating misinformation using machine learning. His recent work emphasizes leveraging clinical trials and biomedical literature to predict treatment efficacies through computational frameworks. Key Contributions: First inventor on a molecule ranking patent (2021), co-developer of the CovidX algorithm for drug repurposing, and supervisor of PhD students/postdoctoral fellows. Collaborates with Sano teams to advance clinical research through AI. Awards: FastCompany Most Creative (2016) Industry Impact: Contributed to a multi-million dollar grant for a recommendation engine startup. Labs/Teams: Currently part of Sano's research teams, focusing on computational clinical research and interdisciplinary collaborations.

Joanna RadomskaView profile

Professor

• Strategic Management
• Open Strategy
• Creative Industries
• +3 more

Joanna Radomska is a Professor at the Department of Strategic Management within the Management Department at Wrocław University of Economics. Her research focuses on strategic management, open strategy, creative industries, and omnichannel strategies. She actively supervises doctoral students and contributes to academic discourse through numerous publications. Key themes include cross-industry cooperation, organizational resilience, and digital transformation challenges in retail and creative sectors. Her work spans empirical studies on coopetition dynamics, family firm resilience, and the integration of ICT in business strategies. Notable contributions address omnichannel retailing obstacles, open innovation frameworks, and the interplay between strategic approaches and operational risks. Publications highlight her expertise in strategic dilemmas, innovation ecosystems, and the application of predictive analytics in food demand forecasting. Despite no listed awards, her extensive body of work reflects significant scholarly impact in strategic management and organizational studies.

• Building Automation Systems
• Smart Grid Technologies
• Renewable Energy Integration
• +5 more

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 PłotkaView profile

Researcher

• Medical Imaging
• Deep Learning
• Computer Vision
• +3 more

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).

Jacob FishView profile

Professor

• Computational Mechanics
• Multiscale Modeling
• Structural Engineering
• +3 more

Jacob Fish holds the Rosalind and John J. Redfern Jr. Chair in Engineering at Columbia University's Department of Civil Engineering and Engineering Mechanics within the Fu Foundation School of Engineering and Applied Science. His research program focuses on computational mechanics and multiscale modeling with applications across material science and structural engineering. His research interests center on developing advanced computational frameworks for multiscale analysis of heterogeneous materials. Key areas include computational continua, atomistic-to-continuum coupling, fracture mechanics of composites, and thermomechanical modeling of advanced materials. His work bridges theoretical developments with practical engineering applications through reduced-order modeling and data-physics integration. His recent publications demonstrate strong trends in multiscale computational engineering, particularly in homogenization techniques, phase-field fracture modeling, and data-driven approaches for material behavior prediction. The research spans from atomistic simulations to structural-scale analysis with emphasis on computational efficiency and physical fidelity. Fellow, U.S. Association for Computational Mechanics (USACM) Computational Structural Mechanics Award, 2005 Fellow, International Association for Computational Mechanics (IACM), 2002 National Science Foundation Presidential Young Investigator Award, 1992 Walter P. Murphy Fellowship, Northwestern University, 1986 Fish serves as Editor-in-Chief of the International Journal for Multiscale Computational Engineering and has secured numerous research grants focused on multiscale modeling of advanced materials. His collaborative network spans multiple institutions and disciplines, particularly in computational mechanics and material science. His laboratory develops computational frameworks for multiscale analysis with applications in structural engineering, material science, and biomechanics, focusing on efficient algorithms for complex material behavior prediction.

• Information and Communication Technology
• Electrical and Electronic Engineering
• Artificial Intelligence
• +3 more

Paweł Tarnowski is a researcher at the Institute of the Theory of Electrical Engineering, Measurement and Information Systems , Faculty of Electrical Engineering, Warsaw University of Technology. His work focuses on biomedical signal processing, emotion recognition, and machine learning applications in affective computing and human-computer interaction. Research areas include Information and Communication Technology (ICT) Electrical and Electronic Engineering Artificial Intelligence Neuroscience Human Factors His recent publications highlight trends in emotion recognition using multimodal physiological signals (EEG, EOG, GSR), driver fatigue detection, and deep learning techniques like 1D-CNN for medical diagnostics. Articles also address urban traffic monitoring and neuromarketing research via EEG analysis. At Warsaw University of Technology, he supervises thesis projects and contributes to interdisciplinary research in biomedical engineering and signal processing. Labs/Teams: Institute of the Theory of Electrical Engineering, Measurement and Information Systems .

Lucyna NykaView profile

Professor

• Urban Flood Resilience
• Nature-Based Solutions
• Waterfront Design
• +3 more

Prof. Lucyna Nyka serves as Professor and Head of the Department of Urban Architecture and Waterfront Spaces at the Faculty of Architecture, Gdańsk University of Technology. Her leadership role encompasses academic administration and research direction within this specialized department focused on climate-resilient urban design. Her research interests center on urban flood resilience , nature-based solutions , and waterfront adaptation strategies in the face of climate change. She employs advanced methodologies including GIS spatial analysis , multi-objective optimization algorithms , and comparative urban studies to develop practical frameworks for sustainable urban development. Her work bridges theoretical research with real-world implementation through numerous international projects. Recent publication trends reveal a strong focus on climate-sensitive urban environments , particularly examining the intersection of walkability and flood resilience in waterfront public spaces across the Baltic Sea Region. Her research portfolio demonstrates consistent evolution from theoretical explorations of architecture-water relationships toward actionable strategies for climate adaptation, with increasing emphasis on nature-based solutions and spatial optimization techniques since 2020. Prof. Nyka leads significant international research initiatives including the Horizon 2020 project 'SOS Climate Waterfront' (agreement 823901) and the 'Premium on the Horizon' funded initiative, both focused on improving waterfront adaptation strategies to climate change. Additional projects include 'Urban ElemenTREE' for smart green space development and the 'ENACT 15mC' initiative for neighborhood co-creation within the 15-minute city framework. Her department actively engages in practical implementation through projects like the revitalization of Potok Królewski stream on the university campus, demonstrating integration of academic research with tangible urban interventions. Current work emphasizes data-driven approaches to climate adaptation, particularly through nature-based solutions that address both flood risk and socio-economic considerations in urban planning.