جست‌وجوی استاد و پژوهشگر

• Social Network Analysis
• Complex Systems
• Statistical Physics
• +۳ مورد دیگر

Janusz Hołyst is a Professor at the Center of Physics in Economics and Social Sciences, Faculty of Physics, Warsaw University of Technology. His research focuses on complex systems, social network analysis, and computational models of collective behavior. He leads the research team Zespół Fizyki w Ekonomii i Naukach Społecznych . Key areas include structural balance dynamics, opinion formation, and interdisciplinary applications of statistical physics. Recent work explores polarization, misinformation, and emotional dynamics in online communities. Over 200 publications span topics from multiplex networks to source localization in complex systems. Education: Not explicitly listed but inferred through academic career. Research interests emphasize bridging physics and social sciences, with contributions to models of group behavior, network hierarchies, and computational sociology. His work highlights critical phenomena in social systems and applications of agent-based simulations. Collaborations include studies on collective emotions, cyberemotions, and the impact of digital media on societal dynamics. Articles often analyze network structures, phase transitions in social models, and methodological advancements in source localization. His team’s projects address real-world challenges like misinformation spread and systemic risk in supply chains. Recipient of grants for supercomputing simulations of social systems and computational science initiatives. Advised numerous theses (names not listed here) focusing on interdisciplinary applications of physics.

• Business Process Modeling
• Ontology in Legal Systems
• Legal Knowledge Management
• +۵ مورد دیگر

Andrzej Greńczuk is an Assistant at the Department of Business Intelligence in Management at Wrocław University of Economics. He holds a Master's degree in Administration from the University of Wrocław (2007-2017), a Bachelor's in Business Computer Science from UEW (2014-2017), and a Master's in UEW (2020-2022). He is currently pursuing a PhD at UEW's Doctoral School since 2022. His primary roles include academic support and research in legal informatics and AI-driven knowledge systems. Education Pathway: Bachelor's in Administration (Local Government), 2004-2007 Long-cycle Law, Administration & Economics program (University of Wrocław), 2007-2017 Bachelor's in Business Computer Science (UEW), 2014-2017 Master's in UEW (supervised by Dr. Iwona Chomiak-Orsa), 2020-2022 PhD Candidate at UEW Doctoral School since 2022 Research focuses on legal informatics, ontology-based systems, AI in legal processes, semantic networks, and ICT applications in judiciary and smart city management. Key themes include knowledge management systems, process modeling (BPMN/UML), and visualization tools for legal data. Recent publications (2022–2024) emphasize AI-driven solutions for legal translation, knowledge base creation via LLM/RAG architectures, and semantic networks in problem categorization. He also explores ICT in smart city infrastructure and renewable energy systems. Collaboration with socio-economic entities: Open to partnerships aligning with his research in legal tech, AI applications, and smart urban systems. Proficient in English and Polish.

Piotr Napieralskiمشاهده پروفایل

دانشیار

• Computer Graphics
• Virtual Reality
• Computer Games
• +۷ مورد دیگر

Piotr Napieralski serves as Associate Professor and Head of the Computer Graphics and Multimedia Department at Lodz University of Technology's Institute of Computer Science, where he has maintained continuous academic employment since 2000. His institutional leadership and research activities position him as a key figure in Poland's computer graphics research community. His research program centers on computer graphics, virtual reality, and game development with significant extensions into mobile systems and human-computer interaction. Core specialties include 3D graphics programming, computer animation, simulation/visualization techniques, and user interface design. Recent work increasingly integrates artificial intelligence methodologies while maintaining strong foundations in geometric algorithms and real-time rendering systems. Analysis of his 2021-2025 publications reveals a dual trajectory: continued innovation in graphics fundamentals (stereo vision consistency, 3D point cloud segmentation, procedural content generation) alongside strategic expansion into interdisciplinary applications including power electronics (solid-state transformers), transportation optimization (AI-driven ecodriving), and behavioral science (eating behaviors, mineral policy). This reflects deliberate diversification while preserving computer graphics as the unifying thread. Dr. Napieralski actively secures research funding through participation in numerous EU-funded projects and serves as a long-term expert for Poland's National Centre for Research and Development (NCBR). His teaching responsibilities include computer graphics instruction for both Polish and international students, though specific student mentorship details are not documented in available sources. As department head, he oversees research directions and educational programs in graphics, games, and multimedia technologies. His leadership fosters collaboration between theoretical computer science and practical industrial applications, particularly in virtual reality systems and mobile gaming platforms where his publications demonstrate consistent output.

• Quantum Computing
• Hybrid Quantum-Classical Algorithms
• Workflow Scheduling
• +۳ مورد دیگر

Katarzyna Rycerz is a Lecturer at the Institute of Computer Science within the Faculty of Computer Science at AGH University of Science and Technology in Kraków, Poland. She holds the academic rank of Lecturer as part of the assistant professors group, with her office located at D-17, ul. Kawiory 21, room II, 3.54. Her research spans quantum computing, hybrid quantum-classical algorithms, and distributed systems, with significant contributions to workflow scheduling and complex network optimization. Dr. Rycerz's primary research focuses on quantum optimization techniques, particularly quantum annealing and variational algorithms applied to combinatorial problems. Her work bridges theoretical quantum computing with practical high-performance computing challenges, including load rebalancing in HPC systems and community detection in complex networks. She has developed software tools like QHyper for hybrid quantum-classical optimization and explored quantum solutions for thermoelectric properties in graphene and quantum game theory paradoxes. Her 15 most recent publications (2019-2025) reveal a dominant trend toward quantum-classical hybrid methods, with 80% focused on quantum annealing applications for workflow scheduling, network analysis, and optimization problems. Key themes include D-Wave system implementations, quantum game theory extensions, and thermoelectric material simulations, demonstrating a consistent shift from earlier multiscale simulation work toward cutting-edge quantum computing applications. No scientific awards are documented in the available information. Details regarding student advising, research grants, laboratory affiliations, or collaborative teams are not provided in the source materials.

• Mutation Testing
• Model Validation
• Software Engineering
• +۹ مورد دیگر

Dr. Eng. Joanna Strug is a lecturer at the Department of Automation and Computer Science within the Faculty of Electrical and Computer Engineering at Cracow University of Technology. Her research focuses on software testing methodologies, machine learning applications in test automation, and database technologies. Specialization in mutation testing and fault injection Expertise in UML/OC validation and business process testing Active researcher in relational and non-relational database modeling Recent research trends indicate a focus on database technology performance analysis, including: Comparative benchmarking of relational vs. NoSQL databases Cost optimization in mutation testing using machine learning Structural similarity applications for test classification Validation frameworks for service-oriented architectures Model-based testing of business processes Bytecode-level mutant classification Her work appears in prominent venues including: Information Systems Architecture and Technology Artificial Intelligence and Soft Computing Journal of Engineering International Conference on Software Engineering (ENASE)

• Artificial Intelligence
• Data Mining
• Machine Learning
• +۷ مورد دیگر

Dr. M. M. El-Gayar is a faculty member at Mansoura University, affiliated with the Faculty of Computer and Information and the Department of Computer Science. He is also associated with New Mansoura University, reflecting his active role in Egypt's evolving academic landscape in computer science and engineering. His research spans key domains in modern computing, focusing on Artificial Intelligence , Data Mining , Deep Learning , and their applications in healthcare , cybersecurity , and the Internet of Things (IoT) . His work integrates computational intelligence to solve real-world problems such as disease diagnosis, medical image analysis, and secure digital systems. The recent publications highlight a strong trend toward applying hybrid and deep learning models in medical diagnostics, including breast cancer and heart disease prediction, as well as semantic analysis for pneumonia detection in pandemic contexts. His IoT research emphasizes optimization for device localization, while cybersecurity efforts focus on phishing mitigation. These interdisciplinary efforts reflect a cohesive research vision centered on intelligent systems for societal benefit. Dr. El-Gayar has received research support from prestigious organizations including the United States Agency for International Development and the British Council , underscoring the international relevance and impact of his work. He has contributed to multiple high-impact journals such as IEEE Access , Computers, Materials and Continua , and the International Journal of Electrical and Computer Engineering , demonstrating consistent scholarly output and collaboration.

• Computational Chemistry
• Structural Biology
• Biophysics
• +۳ مورد دیگر

Tamar Schlick is a Professor at New York University, affiliated with the Courant Institute of Mathematical Sciences and the Department of Chemistry. She holds roles as an Associate (Lead) Editor for the International Journal for Multiscale Computational Engineering and has contributed to numerous journals. Education: B.S. in Mathematics, Wayne State University (1982) M.S. and Ph.D. in Applied Mathematics, Courant Institute of Mathematical Sciences, NYU (1984 and 1987) Research Interests: Tamar Schlick focuses on biomolecular modeling, chromatin dynamics, RNA structure prediction, and computational methods for understanding biological systems. Her work integrates computational simulations with experimental data to study complex systems like DNA repair mechanisms, histone interactions, and RNA folding pathways. Her research bridges disciplines such as biophysics, biochemistry, and applied mathematics. Articles Trends: Her recent publications emphasize multiscale modeling in chromatin organization, RNA structural prediction using graph theory, and energy landscapes in biomolecular interactions. These studies highlight advancements in computational tools and their applications in understanding fundamental biological processes. Awards: Over 20 awards, including the John Simon Guggenheim Fellowship (2000-2001), American Physical Society Fellow (2005), and Aspen Health Forum Fellow (2007). Recognitions for contributions to computational chemistry, RNA science, and biomolecular modeling. Advising & Grants: While specific student advisees are not listed, her research groups collaborate on projects funded by NIH, NSF, and other agencies. She leads teams advancing computational frameworks like RAGTOP and CHSalign for RNA structure analysis. Labs/Teams: Active in NYU’s Courant Institute and NYU-ECNU Center for Computational Chemistry, focusing on interdisciplinary research in computational biophysics and molecular modeling.

• Computer Graphics
• Network Programming
• 3D Modeling
• +۴ مورد دیگر

Dr. Wojciech Palacz is a Lecturer at Jagiellonian University, specializing in Computer Graphics, Network Programming, and 3D Modeling. He teaches courses including Computer Graphics, Network Programming, Web Application Design, and Introduction to 3D Modeling. His research focuses on graphical interfaces, mobile networks, and advanced computer graphics techniques. He actively publishes in areas of graph transformation, collaborative design systems, and robot navigation algorithms. His teaching involves both full-time and part-time studies, with courses delivered remotely and asynchronously. He emphasizes practical projects, such as web application design and network programming assignments, requiring students to implement REST APIs and client-server architectures. His courses often involve team projects, simulations, and user interface prototyping. Palacz's recent work includes studies on indoor robot navigation using BIM/IFC models and the application of hierarchical graph systems in creative design. He maintains an active presence in academic collaborations, with publications in journals like Machine GRAPHICS & VISION and conferences like ICAISC.

Katarzyna Grzesiak-Kopećمشاهده پروفایل

استادیار

• Computational Intelligence
• Machine Learning
• Computer-Aided Design
• +۲ مورد دیگر

Katarzyna Grzesiak-Kopeć serves as an Assistant Professor at the Department of Information Technologies, Jagiellonian University in Krakow, Poland. Her academic profile bridges theoretical computer science with biomedical applications through computational intelligence and machine learning research. Education: MSc in Computer Science, Jagiellonian University (2001) PhD in Computer Science, AGH University of Science and Technology (2005) Research Focus: Dr. Grzesiak-Kopeć specializes in Computational Intelligence and Machine Learning applied to Biomedicine , particularly melanoma diagnostics and gene expression analysis. Her work integrates Diagrammatic Reasoning and Agent-Based Systems for creative design solutions, demonstrating interdisciplinary innovation across cognitive science and medical engineering. Publication Trends: Her 2006-2010 publications reveal consistent exploration of machine learning for biomedical image classification (melanoma detection), pattern discovery in biological data, and agent-assisted design systems. Key methodologies include wavelet transforms, hypergraph operations, and multiobjective optimization algorithms applied to healthcare and spatial planning challenges. Awards: Best Paper Award at Human System Interaction Conference Academic Contributions: Actively supervises Master's theses while teaching Software Engineering, Theoretical Foundations of Computer Science, and AI in Games. Participates in major research initiatives including Monte Carlo Simulations for CTA, Melanoma Computer-Aided Diagnostics, and Embedded Systems co-synthesis through grants like BASTION, PRELUDIUM, and KBN. Associated with Juna Network Academy for academic collaboration.

Grzegorz Gutowskiمشاهده پروفایل

پژوهشگر

• Algorithms
• Graph Theory
• Combinatorics
• +۳ مورد دیگر

Grzegorz Gutowski is a researcher at the Department of Algorithmics, Faculty of Mathematics and Computer Science, Jagiellonian University. His research focuses on algorithms, graph theory, combinatorics, and computational complexity. He holds a Ph.D. in Computer Science from Jagiellonian University (2012). His work includes studies on graph coloring, online algorithms, combinatorial optimization, and algorithmic game theory. Key Research Themes: Graph coloring problems (e.g., online coloring, group coloring, interval coloring) Algorithmic complexity analysis Combinatorial game theory (e.g., slow-coloring games) Transportation network algorithms (e.g., Dial-a-Ride problems) Recent Publications Trends: Recent work emphasizes applications in graph theory, particularly in coloring and structural graph analysis. Notable contributions include studies on treewidth in planar graphs, mixed interval graphs, and combinatorial problems posed by Steinhaus. Awards & Grants: Principal Investigator for grants on algorithmic Nullstellensatz (2020-2025), smart transportation systems, and colonoscopy diagnostics Academic Activities: Supervises graduate research in algorithmics Active in organizing workshops and conferences on theoretical computer science Member of the Algorithmics Research Group at Jagiellonian University

• Combinatorics
• Graph Theory
• Discrete Mathematics
• +۵ مورد دیگر

Piotr Micek is a Professor at the Department of Algorithmics, Faculty of Mathematics and Computer Science, Jagiellonian University. He holds a habilitated doctorate and focuses on combinatorics, graph theory, and discrete mathematics. His research spans graph coloring, probabilistic methods, approximation algorithms, and structural graph theory. He has led multiple grants including 'Order and Geometry' (2023–2027) and 'Structural Theory of Posets' (2020–2023). His work bridges theoretical foundations with algorithmic applications in combinatorial geometry and posets. Education: PhD in Mathematics (2008), Habilitation in Computer Science (2020). Research interests include poset dimension, graph algorithms, and combinatorial geometry. He collaborates internationally and has published over 70 papers in top journals/conferences like Journal of the ACM and Combinatorica . Grants include funding from the National Science Center (NCN) for projects on poset dimensions (2023–2027) and structural theory (2020–2023). Advised PhD student Michał Seweryn. His lab, the Algorithmics Research Group, explores foundational and applied aspects of discrete mathematics.

• Graph Theory
• Algorithms
• Discrete Geometry
• +۳ مورد دیگر

Bartosz Walczak is a Professor in the Department of Algorithmics at the Faculty of Mathematics and Computer Science, Jagiellonian University in Kraków, Poland. His research focuses on Graph Theory, Algorithms, and Discrete Geometry, with a strong emphasis on structural and algorithmic aspects of graphs and their geometric representations. Education and Positions: MSc in Computer Science (2008), Jagiellonian University PhD in Computer Science (2012), Jagiellonian University Postdoctoral Fellowship (2013–2014), École Polytechnique Fédérale de Lausanne (EPFL), Switzerland Visiting Assistant Professor (2014–2015), Georgia Institute of Technology, USA Habilitation in Computer Science (2017), Jagiellonian University Gastprofessor (2017–2018), Technische Universität Berlin, Germany Research Interests: Graph Coloring and χ-boundedness Geometric Intersection Graphs Combinatorial Geometry and Algorithms Graph Algorithms and Complexity Key Achievements: Recipient of the Best Paper Award at WG 2025 for work on Burling graphs Pioneering contributions to solving Ringel's circle problem Advances in separator theorems for planar hyperbolic graphs Labs/Teams: Active member of the Algorithmics Research Group, collaborating with international institutions such as EPFL, Georgia Tech, and TU Berlin.

• Statistical Physics
• Network Science
• Social Dynamics
• +۳ مورد دیگر

Anna Chmiel serves as an Assistant Professor at the Faculty of Physics, Warsaw University of Technology, where her research bridges statistical physics with social dynamics through computational modeling of complex systems. Her work demonstrates significant contributions to understanding collective phenomena in networked environments, particularly through interdisciplinary applications of physical models to social science questions. Her primary research domains include: Statistical Physics of Social Dynamics Multiplex and Polarized Network Analysis Opinion Dynamics and Phase Transitions Collective Emotions in Online Communities Epidemic-Opinion Co-evolutionary Systems Anomalous Diffusion Processes Analysis of her 15 most recent publications (2016-2025) reveals a methodological trajectory from foundational network studies toward sophisticated multiplex frameworks. Key innovations include modeling temperature-noise interplay in opinion dynamics (2025), documenting phase transition 'zoology' in asymmetric q-voter systems (2020), and pioneering cyberemotions research (2016-2017). Her work consistently examines critical phenomena in coupled dynamical processes, with recent emphasis on time-scale dependencies in epidemic-opinion co-dynamics (2022) and structural properties of layered networks (2018). No scientific awards or major honors are documented in available institutional records. Available materials indicate no formal graduate student supervision roles or externally funded research grants. Her institutional profile focuses exclusively on research outputs without mention of mentorship activities or grant leadership. Dr. Chmiel's theoretical work appears integrated within the Faculty of Physics' broader computational research initiatives. No dedicated laboratory or named research team is specified, suggesting collaborative engagement with university-wide physics and interdisciplinary research groups focused on complex systems.

Marcin Pietranikمشاهده پروفایل

استادیار

• Ontology Alignment and Evolution
• Semantic Web Technologies
• Fuzzy Logic Applications
• +۳ مورد دیگر

Marcin Pietranik is an Assistant Professor at the Department of Applied Informatics within the Faculty of Information and Communication Technology at Wroclaw University of Technlogy . His work focuses on ontology alignment, evolution, and semantic web technologies, with applications in artificial intelligence and data integration. Research Interests : Ontology alignment, fuzzy logic frameworks, automatic knowledge integration, and semantic distance metrics. Affiliation : Wroclaw University of Technlogy, Faculty of Information and Communication Technology, Department of Applied Informatics. Article Trends (15 most recent): Ontology alignment methods using fuzzy logic and semantic attributes Applications of machine learning to fake news detection Business rule validation against domain specifications Deep learning for agricultural tasks (grapevine growth stages) Consensus-building algorithms in multi-agent systems

Piotr Sankowskiمشاهده پروفایل

استاد

• Algorithms
• Machine Learning
• Graph Theory
• +۵ مورد دیگر

Piotr Sankowski is a Professor at the Institute of Informatics, University of Warsaw, specializing in algorithms and theoretical computer science with applications in economics and machine learning. He is also CEO of MIM Solutions, deploying ML solutions, and heads the IDEAS NCBR center for AI and Digital Economy. His research focuses on algorithm design, computational complexity, and interdisciplinary applications in physics and economics. Education & Affiliations: Professor at University of Warsaw's Faculty of Mathematics, Informatics, and Mechanics (MIM) Head of IDEAS NCBR Center (Artificial Intelligence & Digital Economy) CEO of MIM Solutions (AI/ML consulting) Research Interests: Piotr's work bridges theoretical computer science and practical applications, with key areas: Algorithms for matching problems, graph theory, and optimization Machine learning explainability and feature importance Quantum tunneling phenomena in semiconductor nanostructures (physics) Algorithmic game theory and network design His ERC grants highlight contributions to algorithmic foundations and interdisciplinary research. Grants & Awards: ERC Starting (2010), Proof of Concept (2015), and Consolidator (2017) Grants First Pole to secure three ERC grants Fellow of the Institute of Informatics at University of Warsaw Publications: Over 80 papers spanning CS (algorithms, ML) and physics (solid-state theory). Recent work focuses on online algorithms, dynamic graph problems, and scalable ML systems. Labs & Projects: Leads the IGAFIT initiative promoting algorithms in Europe, and the EXALT project for explainable optimization tools. Active in the IDEAS NCBR center for AI innovation.