Robert Benke 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 research focuses on graph-based machine learning methodologies and their practical implementations. His core research domains include: Graph Neural Networks Machine Learning Natural Language Processing Graph Analytics Deep Learning Hardware Acceleration Recent publications reveal concentrated efforts in optimizing Graph Convolutional Networks for specialized hardware architectures (Intel PIUMA), addressing critical challenges in memory efficiency and computational scalability. His work bridges theoretical graph analytics with real-world applications in text classification, demonstrating how graph structures capture complex dependencies in unstructured data through neural network approaches.
Prof. Izabela Lubowiecka serves as a Professor at the Department of Structural Mechanics within the Faculty of Civil and Environmental Engineering at Gdańsk University of Technology. Her office is located in the Main Building (room 467A) with contact details including email lubow@pg.edu.pl and phone (58) 348 64 08. She maintains an active research profile with current projects and recent publications through 2025. Her research spans computational biomechanics with specific focus on abdominal wall mechanics, hernia repair systems, and temporomandibular joint analysis. She integrates structural engineering principles with medical applications through advanced computational modeling, uncertainty quantification, and machine learning techniques. Key methodologies include Self-Organising Maps for biomechanical data clustering and digital image correlation for in vivo strain analysis, targeting improvements in medical device design and surgical outcomes. Recent publications (2023-2025) demonstrate consistent interdisciplinary work bridging engineering and clinical medicine. Core themes include mechanical compatibility optimization of hernia implants, failure analysis of surgical mesh systems, and machine learning applications for identifying biomechanically similar tissue regions. This research emphasizes patient-specific modeling through uncertainty quantification and sensitivity analysis to address clinical challenges like hernia recurrence. Prof. Lubowiecka secures significant research funding through national programs: Mechanics of anterior abdominal wall in optimisation of hernia treatment : OPUS project (UMO-2017/27/B/ST8/02518) since 2018 3D-JAW : TMJ modeling for dental applications (POIR.04.01.02-00-0029/17-00) since 2017 Geometric-strength analysis of historical carpentry joints : OPUS project (UMO-2015/17/B/ST8/03260) since 2016 She leads a research team collaborating with medical professionals on translating computational biomechanics into clinical solutions for hernia repair and dental prosthetics, with emphasis on practical implementation of research findings.
Dr. Anna Jakubczyk-Gałczyńska serves as an Assistant Professor in the Department of Civil Engineering at the Faculty of Civil and Environmental Engineering, Gdańsk University of Technology. Her academic work bridges traditional civil engineering with advanced computational techniques, focusing on practical applications that address contemporary challenges in structural analysis and construction management. Her research interests span multiple interdisciplinary domains including structural engineering, machine learning applications, vibration analysis, and construction management optimization. Dr. Jakubczyk-Gałczyńska has developed expertise in applying metaheuristic optimization methods and machine learning algorithms to solve complex engineering problems, particularly in seismic analysis and building vibration assessment. Analysis of her recent publications (2024-2025) reveals a strong trend toward integrating artificial intelligence with traditional civil engineering practices. Her work demonstrates how machine learning can enhance predictive capabilities in structural engineering, particularly in vibration analysis and seismic response prediction, while metaheuristic methods show promise for optimizing construction management processes and decision-making. Dr. Jakubczyk-Gałczyńska has established productive research collaborations with colleagues including M. Mikielewicz, R. Jankowski, A. Siemaszko, and M. Poltavets, resulting in publications in reputable journals such as Applied Sciences-Basel, Bulletin of the Polish Academy of Sciences, and Engineering Applications of Artificial Intelligence.
Agata Siemaszko is an Assistant Lecturer at the Department of Building Engineering, Faculty of Civil and Environmental Engineering, Gdańsk University of Technology. She maintains an active research profile while contributing to academic instruction in civil engineering disciplines. Dr. Siemaszko's research interests span multiple critical areas of modern civil engineering: Bayesian Networks applications in construction management Risk assessment methodologies for urban construction projects Metaheuristic optimization techniques for engineering decision-making Life cycle assessment and cost analysis of building systems Traffic-induced structural vibrations and safety assessment Decision support systems for engineering management under uncertainty Her publication record reveals a clear evolution from foundational risk assessment research to sophisticated computational approaches integrating Bayesian Networks with metaheuristic optimization. This progression demonstrates her commitment to developing practical tools that address the complex, multi-criteria challenges inherent in modern construction management where stakeholders often have conflicting interests. Her most recent work continues to push boundaries with 2025 publications focusing on optimization techniques for building project management. Dr. Siemaszko has earned recognition for her scholarly contributions through several prestigious awards: Second Prize for outstanding publication 'Problems of maintenance of historic bridge structures' at the 14th Scientific Conference of Doctoral Students of Civil Engineering Departments (2014) Winner of the competition for best scientific works concerning the Żuławy region of the Vistula Delta (2012) Third place in the competition for master's and doctoral theses thematically related to the Vistula River (2010) Her research activities include grant-supported work such as the Miniatura 7 grant DEC-2023/07/X/ST8/00317 for vibration measurements of residential buildings. She has contributed to numerous research projects addressing risk management, construction optimization, and structural safety assessment in challenging urban environments. Dr. Siemaszko's laboratory work focuses on structural vibration testing and monitoring, particularly examining how traffic-induced vibrations affect residential buildings. Her approach combines empirical measurement with advanced probabilistic modeling to develop practical risk assessment frameworks for building safety and longevity.
Michał Baranowski serves as an Assistant lecturer at the Department of Microwave and Antenna Engineering within the Faculty of Electronics Telecommunications and Informatics at Gdańsk University of Technology since 2021. He is simultaneously pursuing his PhD at the same institution, demonstrating a strong commitment to both teaching and research in microwave engineering. His research interests focus on advanced microwave component design, particularly in the areas of microwave filters, design optimization techniques, electronic design automation, finite element method applications, computational electromagnetics, and specialized microwave design methodologies. His work bridges theoretical concepts with practical manufacturing approaches, especially regarding additive manufacturing techniques for microwave components. Baranowski's publication record (13 papers from 2020-2025) reveals a clear research trajectory centered on innovative approaches to microwave filter design and waveguide component manufacturing. His most recent work (2024-2025) emphasizes 3D-printed microwave components, shape deformation techniques for resonator design, and methods to improve surface quality of additively manufactured waveguides. This research has direct applications in satellite communications, Earth observation systems, and 5G technology infrastructure. His technical expertise spans computational electromagnetics, optimization algorithms, and advanced manufacturing techniques for high-frequency components, with a particular emphasis on making these technologies more accessible through open platform tools and cost-effective manufacturing approaches. As an active researcher and educator, Baranowski contributes to both the theoretical advancement and practical implementation of microwave engineering solutions, with his work appearing in prestigious journals including IEEE Microwave and Wireless Technology Letters, IEEE Transactions on Microwave Theory and Techniques, and IEEE Access.
Dr. Robert Ostrowski serves as an Assistant Professor at the Department of Algorithms and System Modeling within the Faculty of Electronics, Telecommunications and Informatics at Gdańsk University of Technology. His academic work focuses on theoretical computer science with emphasis on graph-based network problems. His research primarily explores graph theory and distributed algorithms , specializing in multi-agent systems for network security applications. Key investigation areas include heterogeneous agent searching, energy-constrained mobile agents in tree networks, and non-monotone graph searching strategies where traditional monotonicity assumptions do not hold. His work bridges theoretical foundations with practical network security implementations. Dr. Ostrowski's publication record demonstrates consistent focus on algorithmic solutions for network problems. His recent work shows increasing specialization in heterogeneous agent models and energy-aware protocols, with publications appearing in journals like Journal of Computer and System Sciences and Theoretical Computer Science . His academic advising and grant activities are not publicly documented in available sources. Similarly, no scientific awards or fellowships are mentioned in the provided materials.
Krzysztof Oliński serves as an Assistant Professor at the Department of Decision Systems and Robotics within the Faculty of Electronics Telecommunications and Informatics at Gdańsk University of Technology. His academic profile demonstrates a strong focus on control engineering with particular expertise in optimization methodologies for complex dynamic systems. Dr. Oliński's research centers on discrete optimization techniques applied to control theory, with significant contributions to optimal control strategies for nonlinear dynamic processes. His work bridges theoretical foundations with practical industrial applications, particularly in manufacturing and pipeline systems. He has developed innovative approaches including graph-based representations of state-space dynamics and agent-based optimization methods. His keyword profile reveals expertise in computational intelligence, swarm algorithms, and intelligent manufacturing systems, reflecting his interdisciplinary approach to solving complex control problems. An analysis of his publication history from 2007-2012 shows a clear research trajectory evolving from foundational work on fault-tolerant control systems to more sophisticated methodologies like the 'toolgraph' approach. His early publications focused on discrete optimization techniques for control planning, while his later work expanded to include agent-based strategies and integration of natural and artificial intelligence in production systems. His most impactful contributions involve novel representations of state-space dynamics through flow graph structures that enable more effective control strategy design. Dr. Oliński maintains an active research presence with publications in both Polish and international journals including Mathematical Problems in Engineering and the International Journal of Applied Mathematics and Computer Science. His work demonstrates consistent theoretical rigor combined with practical relevance to industrial applications, particularly in intelligent manufacturing systems and pipeline dynamics modeling.
Dr. Eng. Andrzej Gnatowski is a faculty member at the Wrocław University of Science and Technology , affiliated with the Department of Computer Science and Engineering. His research interests span operational research, parallel programming, robust optimization, and neural network-based image analysis. Operational Research Parallel Programming Robust Optimization Image Analysis using Neural Networks His work bridges theoretical optimization techniques with practical applications in computational methods and machine learning, emphasizing scalable solutions for complex systems.
Konrad Kania is a Lecturer at the Department of Quantitative Methods in Management within the Faculty of Management at Lublin University of Technology. He has been working as a researcher and lecturer since 2019, initially at the Faculty of Management at the Faculty of Electrical Engineering and Computer Science, and since 2020 at his current department. His research focuses on applied mathematics, mathematical modeling, data analysis, machine learning, and deep learning, with particular emphasis on tomography applications. Kania's work bridges theoretical mathematical approaches with practical industrial implementations, especially in ultrasound and electrical tomography systems. Analysis of his publications from 2019-2021 reveals a strong focus on developing innovative algorithms for image reconstruction in various tomographic systems. His research spans multiple disciplines including computer science, electrical engineering, physics, and industrial applications, with particular emphasis on real-time processing, anomaly detection, and machine learning applications in tomography. Kania teaches statistical methods, optimization methods, mathematics, and seminars on Using R in Quantitative Methods, demonstrating his commitment to both theoretical and applied aspects of quantitative methods in management education.
