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Piotr Lechowicz is a postdoctoral researcher currently affiliated with Chalmers University of Technology, Department of Computer Science and Engineering, within the College of Engineering. Previously associated with the Department of Computer Systems and Networks (ZSK) at Wrocław University of Science and Technology, he is an active member of the Computer Networks Team and contributes to interdisciplinary research in network optimization and data analysis. His research focuses on advanced optimization techniques in computer networks, particularly in spectrally-spatially flexible optical networks. Key areas include routing, space and spectrum allocation (RSA), migration planning, and fragmentation issues. He applies multi-criteria optimization and evolutionary methods to solve complex network problems and classifier training tasks. Dr. Lechowicz is involved in significant research projects such as Dark-Box Optimization and the development of evolutionary methods for large-scale multi-criteria optimization. His work integrates machine learning, metaheuristics, and application-aware network modeling. He has been recognized with the Secundus Award for academic excellence. His scientific contributions are documented through publications and profiles on Google Scholar and ORCID. Dr. Lechowicz supervises diploma theses and contributes to academic teaching, particularly in research methodologies. He also co-organized the 'Networked Music Performance' concert in 2023, showcasing interdisciplinary collaboration. He is currently conducting a two-year postdoctoral fellowship under Professor Paolo Monti at Chalmers University of Technology, focusing on computer network optimization and automation. His research teams include the Machine Learning Team, Advanced Data Analysis Methods Team, and Metaheuristics Team.

• Network Optimization
• Optical Networks
• Routing and Spectrum Allocation
• +۷ مورد دیگر

Szymon Wojciechowski is an Assistant Professor at the Department of Computer Systems and Networks, Faculty of Electronics, Wrocław University of Science and Technology. He has been actively contributing to research and teaching since October 2019. He is a member of several research teams, including the Machine Learning Team, Metaheuristics Team, and Advanced Data Analysis Methods Team. Faculty of Electronics, Wrocław University of Science and Technology Department of Computer Systems and Networks Machine Learning Team Teaching Team Computer Networks Team His educational background includes a Bachelor of Engineering in Medical Information Systems (2018) and a Master of Engineering in Advanced Informatics and Control (2019), both from Wrocław University of Science and Technology. Dr. Wojciechowski's research focuses on machine learning , particularly in imbalanced data classification , multi-objective optimization , and data stream clustering . He explores data preprocessing techniques and evolutionary algorithms to enhance classifier performance in challenging decision-making scenarios. His work often integrates optimization methods into machine learning pipelines. The recent publications demonstrate a strong trend in applying evolutionary and hybrid AI techniques to solve problems in imbalanced data and network optimization . The research spans domains such as optical networking, semi-supervised clustering, and ensemble classification, indicating a cross-disciplinary approach combining computer networks and intelligent systems. He is actively involved in research projects including IDSTREAM and MOO , focusing on data stream analysis and multi-objective optimization. He completed a research internship at Universidad de Granada, Spain, where he worked on semi-supervised clustering with k-means. He supervises diploma theses and contributes to teaching in computer science and informatics. Dr. Wojciechowski is affiliated with the following research teams: Machine Learning Team Teaching Team Computer Networks Team Advanced Data Analysis Methods Team Metaheuristics Team

• Machine Learning
• Multi-Objective Optimization
• Imbalanced Data Classification
• +۴ مورد دیگر

Maciej Smołka, PhD hab., serves as a University Professor at the Institute of Computer Science within the Faculty of Computer Science at AGH University of Science and Technology in Kraków, Poland. His office is located at D-17, Kawiory 21, room 2.25, and he actively contributes to academic governance through the Computer Science Discipline Council and College of the Faculty of Computer Science. His research centers on computational optimization, specializing in metaheuristics, evolutionary algorithms, and inverse problems. He addresses complex challenges in non-convex optimization, time-delay systems, and stabilization of forward solvers, with significant contributions to hierarchical memetic strategies including the pyHMS Python library. His interdisciplinary work extends to Music Informatics, where he investigates urban soundscapes as carriers of local identity and applies computational methods to musical harmonization. Recent publications (2022-2025) demonstrate advancements in auto-configured metaheuristics for engineering optimization, socio-cognitive approaches to time-delay control, and LLM-generated algorithm design. His work bridges computational intelligence with practical applications in thermal systems and Gaussian mixture modeling, while maintaining a parallel research thread on musicology and urban acoustic ecology.

• Optimization
• Evolutionary Algorithms
• Inverse Problems
• +۴ مورد دیگر

Andrzej Bielecki is a Professor at the Department of Applied Informatics , Faculty of Electrical Engineering, Automatics, Computer Science and Biomedical Engineering, AGH University of Science and Technology in Kraków. His work focuses on interdisciplinary applications of computational systems, neural networks, and structural information theory to biomedical imaging, renewable energy systems, and autonomous robotics. Faculty: AGH University Department: Applied Informatics Research interests span artificial neural networks , systems theory , computational neuroscience , and intelligent monitoring systems for wind turbines and medical diagnostics. His recent publications emphasize structural information encoding , 3D modeling , and statistical signal analysis . Key applications include magnetic resonance image quality assessment , rotary machine fault detection , and unmanned aerial vehicle navigation . While no formal awards or student supervisions are explicitly detailed, his work integrates hybrid AI systems and evolutionary algorithms for complex problem-solving across domains.

• Artificial Neural Networks
• Systems Theory
• Computational Neuroscience
• +۴ مورد دیگر

Piotr Szymczyk is a Professor at the Department of Biocybernetics and Biomedical Engineering , AGH University of Science and Technology in Kraków. His research focuses on artificial intelligence , embedded systems , and real-time data processing , with applications in biomedical engineering, georadar analysis, and energy systems. Key research areas: Neural networks (Laplace/Z-transform), real-time systems , parallel computing , and georadar data classification Projects: NCN grants for 'Intelligent embedded systems' and 'Digital georadar data processing' His work spans embedded Linux , microcontroller programming (ARM, STM32), and wireless technologies (LoRa, Bluetooth LE). He has supervised doctoral and master's theses in these fields. Scientific awards: NCN Agreement No. 6693/B/T02/2011/40 Ministry of Science and Higher Education grant 0128/R/t00/2010/12

• Artificial Intelligence
• Embedded Systems
• Biomedical Engineering
• +۵ مورد دیگر

Ryszard Tadeusiewicz is a Professor at the Department of Biocybernetics and Biomedical Engineering , Faculty of Electrical Engineering, Automatics, Computer Science and Biomedical Engineering , AGH University of Science and Technology in Kraków, Poland. His research spans biomedical engineering, artificial intelligence, and automation, with a focus on medical imaging, neural networks, and healthcare sustainability. Primary research areas: AI-driven diagnostics, biocybernetics, and automated systems Contributions to conferences like ICAISC and journals in medical informatics Leadership in interdisciplinary projects at the intersection of engineering and medicine His recent publications highlight the integration of deep learning with biomedical applications, including tumor segmentation, pneumonia detection, mental health classification, and forest-planting robotics. While no explicit awards are listed, his extensive publication record underscores his role as a thought leader in AI and biomedical innovation.

• Biomedical Engineering
• Biocybernetics
• Artificial Intelligence
• +۳ مورد دیگر

Professor Andrzej Jaszkiewicz is a faculty member at the Faculty of Computer Science and Telecommunications, Poznań University of Technology, where he works in the Institute of Informatics. He holds the position of full professor with extensive experience in multiobjective optimization and evolutionary algorithms, as evidenced by his habilitation completed in 2001 and continuous research output through 2025. Professor Jaszkiewicz's research focuses on theoretical and practical aspects of multiobjective optimization, particularly addressing the challenges of many-objective problems. His work spans quality indicator development (hypervolume, R2), efficient data structures (ND-Trees), evolutionary algorithm design, and applications to combinatorial optimization problems. His publications demonstrate consistent theoretical rigor combined with practical implementation considerations. Recent publications (2022-2025) reveal continued productivity with multiple articles in top journals like IEEE Transactions on Evolutionary Computation and Physics of Fluids. These works explore theoretical properties of quality indicators, efficient calculation methods, and novel applications of optimization techniques to complex problems including fluid dynamics. Professor Jaszkiewicz has supervised doctoral research including Tarek Alkhaeir's 2021 dissertation on software quality metrics and Marek Kubiak's 2009 work on memetic algorithms. He has also reviewed numerous doctoral dissertations in related fields, demonstrating his standing in the academic community and commitment to graduate education. His scholarly output includes journal articles, conference papers, book chapters, and two books. The 2005 edited volume 'Advanced OR and AI methods in transportation' reflects his interest in practical applications of optimization techniques. His research demonstrates sustained scholarly activity from the 1990s to the present, with particular emphasis on advancing the state-of-the-art in multiobjective optimization theory and practice.

• Multiobjective Optimization
• Evolutionary Algorithms
• Combinatorial Optimization
• +۳ مورد دیگر

Dr. Tomasz Białaszewski serves as an Assistant Professor at Gdańsk University of Technology within the Department of Decision Systems and Robotics, Faculty of Electronics, Telecommunications and Informatics. He holds the position of Deputy Head of Department and maintains his office in Building A of the faculty. His research focuses on evolutionary multi-objective optimization, particularly developing quality criteria for highly dimensional optimization problems. Dr. Białaszewski has pioneered innovative approaches using genetic gender concepts to solve complex multi-objective optimization challenges. His work bridges theoretical computational methods with practical applications in decision systems and robotics. Analysis of his recent publications reveals consistent contributions to evolutionary computation methodologies, with particular emphasis on improving evaluation metrics for multi-objective optimization in high-dimensional spaces. His research demonstrates increasing sophistication in handling complex optimization problems through novel algorithmic approaches. Dr. Białaszewski maintains active research collaboration, primarily with Z. Kowalczuk, as evidenced by co-authored publications. His work contributes significantly to advancing computational optimization techniques within the academic community.

• Evolutionary Multi-Objective Optimization
• Genetic Algorithms
• Decision Systems
• +۲ مورد دیگر

Dr. Wojciech Jędruch serves as Associate Professor at the Department of Intelligent Interactive Systems within the Faculty of Electronics Telecommunications and Informatics at Gdańsk University of Technology. His academic profile shows consistent engagement in advanced research at the intersection of artificial intelligence, robotics, and cognitive systems. His research expertise spans multiple critical domains in modern AI development: Machine Learning techniques for dimensionality reduction Architectures for autonomous decision-making systems Self-organization principles in multi-agent frameworks Cognitive modeling for robotic applications Evolutionary approaches to system optimization Dr. Jędruch's work demonstrates strong interdisciplinary connections between computer science, cognitive psychology, and systems theory. Analysis of his publication record reveals a cohesive research trajectory focused on enabling intelligent systems to manage complexity through feature extraction and memory modeling. His work on shepherding problems demonstrates practical applications of autoencoders for managing large-scale agent collectives, while his research on economic modeling in multi-agent systems shows theoretical depth in emergent organizational patterns. As a member of the Department of Decision Systems and Robotics research team, Dr. Jędruch contributes to Gdańsk Tech's legacy in control theory that has evolved into contemporary artificial intelligence research. His work continues the institution's tradition of bridging mathematical systems theory with practical robotic implementations.

• Feature Extraction
• Machine Learning
• Evolutionary Algorithms
• +۷ مورد دیگر

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.

• Discrete optimization
• Control optimization
• Optimal control
• +۶ مورد دیگر

Prof. Elżbieta Czarny is a distinguished Professor at Warsaw School of Economics specializing in International Economics through the Institute of International Economics. Her academic career spans decades of research on European integration, international trade dynamics, and economic competitiveness with particular focus on Poland's position within global value chains and EU structures. Her research program centers on International Economics , European Integration , and Economic Competitiveness with specialized expertise in Visegrad Group economies, German-Polish economic relations, and transatlantic trade frameworks. Key methodological approaches include export structure analysis, competitiveness benchmarking, and geopolitical economic impact assessment. Analysis of her 15 most recent publications (2024-2017) reveals three dominant research trajectories: (1) Real-time assessment of geopolitical shocks on social market economies (Ukraine war impacts); (2) Evolutionary analysis of EU-10 export convergence toward German manufacturing standards; (3) Critical evaluation of transatlantic trade frameworks including TTIP's institutional implications. Her work consistently bridges theoretical trade models with empirical analysis of Eastern European integration. Prof. Czarny maintains active scholarly engagement through editorial leadership, notably co-editing the 2016 volume on EU-US global production networks. Her research demonstrates sustained policy relevance through timely analysis of economic crises, institutional transformations, and geopolitical economic realignments affecting Central Europe.

• International Economics
• European Integration
• International Trade
• +۳ مورد دیگر