Find Academic Supervisors

• Matroids
• Combinatorial algebraic geometry
• Commutative algebra
• +2 more

Michał Lasoń is a researcher in combinatorics and discrete mathematics affiliated with the Faculty of Mathematics and Computer Science at Jagiellonian University. His academic work focuses on matroid theory, combinatorial algebraic geometry, and discrete geometry, with significant contributions to coloring problems and algebraic combinatorics. His research interests include Matroids, Combinatorial algebraic geometry and commutative algebra, Extreme combinatorics, and Discrete geometry. Dr. Lasoń's work often bridges combinatorial structures with algebraic methods, particularly in the study of matroids and their applications to geometric problems. Dr. Lasoń's publication record shows a strong focus on matroid coloring problems, geometric combinatorics, and algebraic approaches to discrete structures. His work spans theoretical foundations to specific combinatorial problems, with publications in top journals including Advances in Mathematics, Proceedings of the American Mathematical Society, and European Journal of Combinatorics. His educational background includes dual PhDs - in Mathematics from the Institute of Mathematics of the Polish Academy of Sciences (2013) and in Computer Science from Jagiellonian University (2014), following an MSc in mathematics from Jagiellonian University in 2008. Dr. Lasoń held postdoctoral positions at Ecole Polytechnique Federale de Lausanne (2013-2014), Free University of Berlin (2014-2016), and University of Bern (2016-2017), establishing an international research profile in combinatorial mathematics.

Arkadiusz TomczykView profile

Researcher

• Image Analysis
• Machine Learning
• Computer Vision
• +5 more

Arkadiusz Tomczyk is a researcher at the Institute of Information Technology of the Lodz University of Technology , where he has worked since 2002. His academic career focuses on image processing , machine learning , and computer vision , with notable contributions to active contour methods and graph neural networks . He has led and collaborated on multiple funded projects, including a National Science Centre grant (2013-2017) on Cognitive Hierarchical Active Partitioning. Education: MSc in Computer Science (2002), PhD in Computer Science (2011) from Lodz University of Technology His research spans convolutional neural networks , transformers , and graph neural networks , with applications in medical imaging and natural image analysis . Recent work emphasizes structured prediction and explainability in attention mechanisms for chemical molecule analysis. Tomczyk contributes to applied machine learning in projects like METERNET-EnMS (energy management) and FIF (edge devices for zero-emission goals). He teaches object-oriented programming , deep learning , and supervises laboratory infrastructure projects.

• Data Visualization
• Computational Biology
• Tumor Modeling
• +3 more

Rafał Wcisło serves as a Lecturer at the Institute of Computer Science within the Faculty of Computer Science at AGH University of Science and Technology in Kraków, Poland. His academic profile combines teaching responsibilities with active research in computational methods for data visualization and biomedical simulation, contributing to the university's reputation in computer science and interdisciplinary applications. Dr. Wcisło's research centers on innovative approaches to visualizing high-dimensional data and modeling complex biological systems. He has pioneered GPU-accelerated techniques for embedding large datasets and developed the Particle Automata Model (PAM) for simulating tumor dynamics and pathogen expansion. His work in medical applications extends to stroke rehabilitation, where he has designed multimedia holistic methods for patient recovery. These diverse interests reflect a commitment to solving real-world problems through computational innovation. Analysis of his publication record from 2012-2020 reveals a consistent focus on efficiency and interactivity in visualization tools, with a strong emphasis on GPU parallelism. His research trajectory shows increasing integration of computational biology, particularly in oncology, where his models address tumor progression under anti-tumor treatments. The recurring theme across his work is the development of robust, scalable methods that balance computational demands with practical utility in medical and scientific contexts.

Przemysław GordinowiczView profile

Assistant Professor

• Graph Theory
• Combinatorics
• Discrete Mathematics
• +2 more

Dr. Przemysław Gordinowicz serves as an Assistant Professor at Lodz University of Technology within the Department of Applications of Contemporary Mathematical Analysis. Based in room 161 with contact details (+48) 42 631-36-33 and pgordin@p.lodz.pl, he maintains an active research profile in discrete mathematics. His research centers on Graph Theory and Combinatorics, specializing in graph coloring extendability problems for planar and outerplanar graphs, pursuit-evasion games (cops and robbers, localization games), and polynomial method applications. He also investigates random graph models, discrete Laplacian problems, and extremal graph theory, employing combinatorial and algebraic techniques to solve complex structural problems. Analysis of his 15 most recent publications (2015-2025) reveals consistent focus on three interconnected themes: (1) polynomial method applications to list coloring extendability, (2) theoretical advances in pursuit-evasion games across diverse graph classes, and (3) firefighter problem variants including surviving rate calculations. His work bridges theoretical combinatorics with algorithmic applications, frequently appearing in top-tier journals like Journal of Graph Theory and Electronic Journal of Combinatorics. He has supervised PhD student Paweł Twardowski, whose 2023 dissertation addressed graph polynomial applications to list coloring extendability in planar graphs. No information about research grants or collaborative teams is available in the provided materials.

• Artificial Intelligence
• Business Process Modeling
• Knowledge Engineering
• +9 more

Antoni Ligęza 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 research focuses on artificial intelligence, business process modeling, constraint programming, and knowledge engineering. He actively explores explainable AI methodologies, including grammatical evolution and temporal logic-based approaches.

• Graph Theory Applications
• Smart City Energy Management
• Public Lighting Optimization
• +2 more

Adam Sędziwy 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, Poland. His research focuses on graph-based computational methods for energy conservation in smart city infrastructure, particularly public lighting systems optimization. He maintains an active office in building C-2, room 427, and serves on the Disciplinary Council for Technical Information Technology and Telecommunications. His research expertise centers on: Graph theory applications in urban infrastructure design Energy efficiency optimization for street lighting networks Multi-agent systems for distributed lighting control Computational sustainability balancing light pollution, energy savings, and visibility Reactive power management in large-scale electrical lighting systems Analysis of his 2017-2023 publications reveals a concentrated research trajectory applying graph-based optimization and multi-agent frameworks to public lighting retrofit projects. His work consistently addresses the triad of environmental impact (light pollution reduction), economic efficiency (energy/cost savings), and operational safety across diverse contexts from rural roads to urban smart cities. Methodologically, he integrates computational graph transformations with real-world lighting physics to develop novel control algorithms. Scientific Awards: No awards documented in available sources Advising and Grants: Student supervision details not publicly available Grant funding information not specified in source materials Laboratory Affiliations: Dr. Sędziwy's computational research is conducted within AGH's Department of Applied Informatics, leveraging graph-based knowledge representation frameworks. His publications indicate collaboration with teams specializing in distributed computing for lighting design, though specific lab names are not disclosed in the source text.

• Formal Methods
• Concurrent Systems
• Real-Time Systems
• +7 more

Professor Marcin Szpyrka is a faculty member at AGH University of Science and Technology in Kraków, Poland, where he works in the Department of Applied Informatics within the Faculty of Electrical Engineering, Automatics, Computer Science and Biomedical Engineering. He holds the position of Professor and maintains an office in building C-2, room 321. His academic work spans formal methods, concurrent systems modeling, and data mining applications. Professor Szpyrka's primary research interests focus on formal methods including the Alvis modeling language, Petri nets, and process algebras. He specializes in the modeling and verification of concurrent and real-time systems , with applications spanning industrial processes, automotive diagnostics, and cybersecurity. His work bridges theoretical computer science with practical engineering applications, particularly in embedded systems and data analysis. Analysis of Professor Szpyrka's recent publications reveals a clear research trajectory focusing on formal verification techniques applied to increasingly complex systems. His work has evolved from foundational research on the Alvis language to practical applications in automotive systems, industrial processes, and cybersecurity. The publications demonstrate consistent expertise in modeling concurrent systems while expanding into data mining and machine learning applications for anomaly detection and system diagnostics. Rector's Finance Committee Disciplinary Council for Technical Information Technology and Telecommunications Disciplinary Appeals Committee for Doctoral Students Supervised 9 PhD dissertations between 2009-2024 Developed academic resources including the aghdpl LaTeX class for thesis preparation Mentored students working on formal methods, concurrent systems, and data mining applications Professor Szpyrka leads the Formal Methods research group with projects hosted at fm.kis.agh.edu.pl, focusing on the development and application of the Alvis modeling language for system verification.

• Relational Databases
• Speculative Query Execution
• Distributed Computing
• +5 more

Anna Sasak-Okoń is a Lecturer at the Department of Information Systems Software within the Institute of Informatics and Mathematics , Maria Curie-Skłodowska University (UMCS). Her academic work focuses on database systems, speculative query execution, and distributed computing, with a particular emphasis on graph-based modeling techniques.

• Interactive Computer-Aided Design
• Visual Languages and Design Reasoning
• Graph Knowledge Representation
• +4 more

Dr. Grażyna Ślusarczyk is a Professor at the Department of Design and Computer Graphics at Jagiellonian University, serving as its Head. Her research focuses on interactive computer-aided design systems, graph-based knowledge representation, and evolutionary design methods. She specializes in integrating BIM (Building Information Modeling) with machine learning for architectural and engineering applications. Research Interests: Interactive CAD systems, Visual Languages, Graph Transformations, Evolutionary Design, and Machine Learning in Architecture. Her work bridges computational methods with practical design challenges, emphasizing ontology-based systems and automated design solutions. Publications: Recent work includes advancements in BIM-based applications (2024 review), crisis housing design (2025), and ontology integration for rare disease data (2025). Her research trends highlight interdisciplinary approaches combining AI, graph theory, and architectural design. Labs/Teams: Leads the Department of Design and Computer Graphics, collaborating with teams on projects involving BIM, graph databases, and evolutionary algorithms.

• Computer Science
• Computer-Aided Design
• Graph Theory
• +5 more

Dr. Barbara Strug is an Associate Professor at the Faculty of Mathematics and Computer Science, Jagiellonian University. She specializes in computer-aided design, graph theory, and ontology engineering, with a focus on applications in architecture and engineering. Her work integrates machine learning, BIM technology, and evolutionary algorithms to solve complex design and optimization problems. Research interests include: Graph-based design systems Semantic integration of data Generative architectural design Building information modeling (BIM) Multi-agent systems in design collaboration Recent publications focus on ontology-based data integration for rare diseases, BIM-driven machine learning applications, and generative design methods using graph transformations. She has contributed to over 50 peer-reviewed articles in journals like Automation in Construction and Expert Systems with Applications. Prof. Strug collaborates with institutions like the POLVAS project for rare disease research and has developed tools like GraphTool for visual design support. Her work emphasizes interdisciplinary approaches combining computer science with engineering and architecture.

• Computer Science
• Linguistics
• Digital Humanities
• +5 more

Dr. Iwona Grabska-Gradzińska is an Assistant Professor affiliated with the Faculty of Physics, Astronomy and Applied Computer Science at Jagiellonian University. She holds a PhD in Engineering and Technology (2023) for her work on narrative generation in computer role-playing games using graph transformations. Her research bridges computer science and humanities, focusing on narrative structures in video games, eye-tracking for visual perception analysis, and computational linguistics. Educated in both computer science and Polish philology, her interdisciplinary projects include linguistic analysis of literary texts via scale-free networks (at IFJ PAN), eye-tracking studies for railway visualization simulators, and collaborative design tools for game narratives. She currently participates in the 'Scientific Edition of Piotr Skarga's Writings' project. Her didactic interests span digital photography processing, concept art, data visualization, and interface design. Key contributions include graph-based models for game design, AI-driven story generation frameworks using Godot Engine, and tools for analyzing gameplay through biosignals and oculography. Her work emphasizes graph transformation systems, collaborative creative design, and multimodal interaction analysis. Projects often involve cross-disciplinary collaborations, integrating computational methods with humanities and educational technology.

Mikołaj BojańczykView profile

Professor

• Automata Theory
• Logic in Computer Science
• Monadic Second-Order Logic
• +7 more

Mikołaj Bojańczyk is a Professor at the Institute of Informatics, Faculty of Mathematics, Informatics and Mechanics, University of Warsaw. He has been affiliated with the University of Warsaw since his undergraduate studies, with brief periods at institutions in Bordeaux and Paris (2004-2005). He received his PhD in 2004 under Igor Walukiewicz, completed his habilitation in 2008, and was promoted to full professor in 2014. Professor Bojańczyk's research lies at the intersection of theoretical computer science and mathematical logic, with a strong emphasis on automata theory. His work spans several interconnected domains: formal language theory, algebraic approaches to language recognition, monadic second-order logic and its extensions, polyregular functions, and the theory of atoms for handling infinite alphabets. He has made significant contributions to understanding the connections between logic and automata for various structures including words, trees, graphs, and data words. His research has particularly focused on characterizing logical definability through algebraic means, developing new automata models for complex structures, and exploring the boundaries of decidability for various logical formalisms. Analysis of his recent publications reveals a continued focus on polyregular functions, MSO transductions, and the theory of atoms. His work demonstrates a consistent pattern of connecting category-theoretic approaches with concrete automata models, often bridging abstract mathematical concepts with practical computational frameworks. A notable trend is his exploration of rank-based approaches in logic and graph theory, as well as deepening connections between algebraic structures and logical definability. Salomaa Prize (2024) PODS Test of Time Award (2016) PODS Best Paper (2013) Presburger Award (2010) Kuratowski Award (2007) Lipski Prize (2006) PODS Best Paper (2006) Ackermann Award (2005) ICALP Best Paper (2004) Professor Bojańczyk has successfully supervised numerous PhD students to completion, including Rafał Stefański (2023), Janusz Schmude (2022), and others dating back to Paweł Parys (2011). He currently supervises four ongoing PhD projects with Kacper Lewandowski, Katzper Michno, Antoni Puch, and Omid Yaghoubi. His grant portfolio demonstrates sustained research leadership, including the current NCN Maestro grant "Polynomial finite-state computation" (2023-2028), previous ERC Consolidator Grant "Lipa" (2016-2021), and ERC Starting Grant "Sosna" (2009-2014). He has also been active in academic service, serving on prestigious committees including the Gödel Prize Committee (2024-2026) and the Presburger Award Committee (2021-2023). Professor Bojańczyk has been instrumental in developing the "atoms" research program at the University of Warsaw, which has its own blog and book. This theoretical framework addresses computation with infinite alphabets through the lens of nominal sets and orbit-finite structures. He has also created educational resources including the "Automata Toolbox" lecture notes and the "Slajdomat" slide software for creating zooming presentations in Figma.

• Discrete Optimization
• Combinatorial Optimization
• Approximation Algorithms
• +5 more

Jarosław Byrka is a Professor in the Combinatorial Optimization group at the Institute of Computer Science, University of Wrocław. He has held postdoctoral positions at TU Eindhoven and EPFL, and has been a full professor since 2021. His research focuses on algorithmic and mathematical aspects of discrete optimization problems. Research Interests: His primary research areas include Discrete Optimization, Location and Covering Problems, Network Design, and LP-rounding Approximation Algorithms. He employs advanced techniques such as randomized rounding to develop efficient approximation algorithms for NP-hard problems. His work bridges theoretical foundations with practical applications in network design and resource allocation. The recent publications, such as the 2024 result on the integrality gap of BCR, reflect a strong trend in pushing the limits of approximation guarantees in combinatorial optimization. His research consistently contributes to the theoretical understanding of LP-based methods and their applications in graph and network problems. Scientific Awards: STOC 2010 Best Paper Award Witold Lipski Prize Advising and Grants: He has successfully supervised five PhD students to graduation and mentored several postdoctoral researchers including Joachim Spoerhase, Meesum Syed Mohammad, Martin Boehm, Sandip Banerjee, and Yongho Shin. While specific grant details are not listed, his long-term research productivity and leadership in major conferences suggest sustained funding support. Labs and Teams: He is a key member of the Combinatorial Optimization group at the University of Wrocław, contributing to its international visibility through editorial work and conference organization.

Piotr BródkaView profile

Associate Professor

• Complex Networks
• Social Network Analysis
• Multilayer Networks
• +2 more

Prof. Piotr Bródka is an Associate Professor at the Department of Artificial Intelligence within the Faculty of Computer Science and Telecommunications at Wroclaw University of Science and Technology. His research focuses on modeling and analyzing complex networks, including social networks and water supply systems, with emphasis on dynamic processes like information spread and social influence. His research examines propagation mechanisms in multilayer networks, community evolution, and social network dynamics. Recent publications explore influence maximization strategies, network diffusion frameworks, and applications in epidemiology and social behavior modeling. Scientific Awards: Top500 Innovators Scholarship at Stanford University Scholarship for Young Scientists from Ministry of Science Member of Academia Professorum Iuniorum He leads research projects funded by National Science Centre, EU, and Visegrad Fund, focusing on multilayer network analysis. As former deputy head of the Department of Artificial Intelligence, he supports research team development.

• Tomography
• Image Reconstruction
• Machine Learning
• +2 more

Robert Banasiak is Research Professor at Lodz University of Technology's Institute of Applied Informatics, specializing in industrial tomography and computational imaging. His research develops advanced algorithms for 3D electrical capacitance tomography (ECT) with applications in multiphase flow monitoring and process control. Recent innovations include machine learning classifiers for flow regime identification, GPU-accelerated reconstruction techniques, and 3D-printed sensor designs. Key research areas: Real-time 3D imaging for industrial processes Machine learning applications in tomography High-performance computing for image reconstruction Additive manufacturing of sensor systems Multiphase flow quantification Technological contributions include graph-based reconstruction methods, multi-GPU algorithms for tomographic processing, and development of hybrid ECT/ERT systems. Research addresses fundamental challenges in measurement resolution, computational efficiency, and sensor design for harsh industrial environments.