The conference addresses a number of aspects of Artificial Intelligence, which have been organized into the following thematic tracks:
Data Mining and Machine Learning
Chairs
- prof. Michał Woźniak – Wrocław University of Science and Technology
- prof. Ireneusz Czarnowski – Gdynia Maritime University
- prof. Rafał Doroz – University of Silesia in Katowice
Description
The session is devoted to theoretical and practical aspects of machine learning and data mining, also focusing on different approaches to learning from difficult and complex data and issues related to explaining machine learning models.
Knowledge Engineering
Chairs
- prof. Grzegorz J. Nalepa – Jagiellonian University
- prof. Dariusz Krol – Wrocław University of Science and Technology
- prof. Agnieszka Nowak-Brzezińska, University of Silesia in Katowice
Description
This track welcomes submissions devoted to knowledge engineering methods, tools, resulting resources, and reasoning methods availing of structured knowledge. The topics include but are not limited to: ontologies, knowledge graphs, Semantic Web & Linked Data, ontology design patterns, knowledge modeling and ontology engineering methodologies, knowledge acquisition methods (web scrapping, crowdsourcing, large language models prompting, etc.), knowledge extraction, knowledge graph completion and refinement (entity linking, link prediction, triple classification, etc.), representation learning of knowledge graphs (knowledge graph embeddings), reasoning with logics, commonsense reasoning, provenance in managing semantic data, FAIR data management and knowledge bases quality assessment
Medical Applications of Artificial Intelligence
Chairs
- prof. Włodzisław Duch – Nicolaus Copernicus University, Toruń
- prof. Julian Szymański – Gdańsk University of Technology, Gdańsk
Description
Artificial intelligence (AI) and machine learning (ML) are revolutionizing the medical field through a wide range of applications. These technologies are being leveraged in areas such as molecular biology and drug design, digital pathology, advanced diagnostic methods, therapy planning, and the personalized management of mental health disorders. This track invites discussions and studies on these innovative uses of AI.
Topics of interest include, but are not limited to:
- Identification of medical problems using AI
- Data mining and big medical data analytics
- Biomedical signal and image processing
- Knowledge-based expert systems in medicine
- Natural language processing models for medical document classification and information retrieval
- Patient engagement and support systems
- Ambient assisted living technologies
- Telemedicine and e-health solutions
- Wearable sensors and health trackers
- Predictive data analytics and risk measurement in healthcare.
We welcome contributions that explore these fields and showcase AI’s impact on modern medical practices.
Neural Network and Deep Learning Systems
Chairs
- prof. Aleksander Byrski – AGH University of Science and Technology
- prof. Maria Ganzha – Warsaw University of Technology
Description
The goal of this track is to create a forum for practitioners and adepts doing research on various applications and theoretical aspects of neural networks and deep learning. The topics covered by the track include (but not limited to): classification, prediction, data science, machine learning, feature extraction, image and video processing, medical applications, autonomous vehicles and others.
Natural Language Processing, Automatic Speech Recognition, and Conversational AI
Chairs
- prof. Maciej Piasecki – Wrocław University of Science and Technology
Computer Vision
Chairs
- prof. Leszek Chmielewski – Warsaw University of Life Sciences
- prof. Bogdan Kwolek – AGH University of Science and Technology
Description
The session is organized in cooperation with the Institute of Information Technology, Warsaw University of Life Sciences – SGGW, and the Association for Image Processing, Poland – Towarzystwo Przetwarzania Obrazów.
Uncertainty in Artificial Intelligence
Chairs
- prof. Dominik Ślęzak – University of Warsaw
- prof. Beata Zielosko – University of Silesia in Katowice
Description
This track is a forum for bringing together researchers from academia and business to explore and discuss various approaches to dealing with the uncertainty in a broad range of AI systems and applications. The uncertainty can refer to indeterminism, incompleteness, vagueness, and many other aspects related to knowledge, information, and data. The elements of reasoning under uncertainty can be found in many practical areas, such as data science, robotics, simulations, video game industry, and so on.
We welcome the topics related to theories, methodologies, and applications in the fields of machine learning, knowledge representation, reasoning under uncertainty, and multi-agent systems. We also encourage contributions dedicated to probabilistic graphical models, fuzzy logic, rough sets, information granulation, and others. Last but not least, when it comes to machine learning, we are particularly interested in new approaches to estimation and utilization of aleatoric and epistemic uncertainty.
Robotics and Autonomous Systems
Chairs
- prof. Piotr Lipiński – Lodz University of Technology
- prof. Piotr Skrzypczyński – Poznan University of Technology
- prof. Cezary Zieliński – Warsaw University of Technology
Description
The track is devoted to the methods, algorithms and applications that belong to the broadly understood Artificial Intelligence and adaptive systems in robotics and related areas including but not limited to: autonomous vehicles, drones, human-machine interfaces including AR/VR, and various types of embodied agents. Artificial intelligence methods and algorithms, especially machine learning methods, are key factors in the progress of modern robotics. At the same time, many initiatives (e.g. the AI, Data and Robotics Partnership in Horizon Europe and Adra) emphasize the need for cooperation of various research and industrial communities that draw on the achievements of AI and apply AI-based methods in engineering, which we hope can be achieved thanks to the participation in this track. Therefore, we invite you to submit works for PP-RAI 2025 in the RAS track.
Problem Solving and Optimisation
Chairs
- prof. Jarosław Arabas – Warsaw University of Technology
- prof. Karol Opara – Systems Research Institute, Polish Academy of Sciences
- prof. Szymon Łukasik – AGH University of Science and Technology
Description
The track is related to algorithmic advances in optimization and metaheuristics, such as theoretical results, algorithm design, parameter tuning and performance evaluation. Topics of interest also include problem-solving, application studies and all issues arising at the interface of modeling and optimization.
Artificial Intelligence in Bioinformatics
Chairs
- prof. Dariusz Plewczyński – Warsaw University of Technology
- prof. Tomasz Gambin – Warsaw University of Technology
- prof. Robert Nowak – Warsaw University of Technology
Description
The „Artificial Intelligence in Bioinformatics” (AIB) track, organized in cooperation with the Genomics Platform at WUT, is dedicated to the exploration and discussion of the innovative development of AI techniques within the field of bioinformatics. The track will focus on the application of AI to analyze biological data and advancing our understanding of complex biological systems, which is crucial for breakthroughs in genetics, molecular biology, and personalized medicine. Recognizing the interdisciplinary nature of the field, the AIB track encourages submissions that demonstrate the integration of AI methods with biological insights, fostering collaboration between computational researchers, mathematicians, geneticists, and biologists. Participants will have the opportunity to present their latest research, discuss methodological advances, and debate the future directions of AI in bioinformatics.
The AIB track aims to cover a broad spectrum of topics, including but not limited to AI applications in:
- sequence analysis
- structural and systems biology
- functional genomics
- population and comparative genomics
- integration of multi-omics data
- personalized medicine
- metagenomics
- synthetic biology
- ML supports for drug discovery
- scalable genomics in cloud-based environments
- chemoinformatics, drug design and biomarker discovery
- scientific literature and textual annotation mining
Generative Artificial Intelligence
Chairs
- prof. Maciej Zięba – Wroclaw University of Technology
- prof. Przemysław Spurek – Jagiellonian University
- prof. Urszula Boryczka- University of Silesia in Katowice
Description
This track is focused on the theoretical foundations and practical aspects of generative models. We welcome outstanding works from various domains, including vision, text, sound, 3D representations, and other data modalities. We are especially interested in novel architectures and applications of diffusion models, GANs, VAEs, normalizing, LLMs, efficient methods in training, fine-tuning, distillation, and quantization of generative models, continual learning for generative models, generative models for uncertainty modeling, prompt engineering techniques and many other topics related to generative modeling.
Interdisciplinary Topics in Artificial Intelligence
Chairs
- prof. Adam Wojciechowski – Lodz University of Technology
- prof. Jarosław Wąs – AGH University of Science and Technology
- prof. Maciej Grzenda – Warsaw University of Technology
Description
The track is a response to the ever-growing applications of artificial intelligence in interdisciplinary research. The scope of the track includes and is not limited to:
- food and nutrition technology;
- energy saving and sustainability;
- game development; – material engineering;
- mechanical engineering and mobility;
- business and economy;
- chemical sciences;
- construction and architecture.
Young.AI (session for young researchers)
Chairs
- mgr Stanisław Kaźmierczak – Warsaw University of Technology
- dr Adam Żychowski – Warsaw University of Technology
- dr Tomasz Orczyk – University of Silesia in Katowice
- dr Tomasz Wesołowski – University of Silesia in Katowice
Description
This track is an opportunity for young researches and students to present their ideas, methods, solutions and applications making use of artificial intelligence. The topics of interest include, but are not limited to, the following themes: machine learning, neural networks and deep learning, fuzzy logic and fuzzy systems, multi-agent systems, robotics, autonomous systems, expert systems, evolutionary computation, reasoning, knowledge representation, planning, learning, natural language processing, perception. The track will constitute a forum of thoughts, ideas and experiences exchange, especially intended for young scientists, so the concepts related to AI at different stages of their development, from very initial phase, through the development stage, up to the final stage of implementation and testing, are all warmly welcomed.
Reports on AI Business Projects (session for Business Pass participants)
Chairs
- prof. Michał Woźniak – Wroclaw University of Technology
- prof. Jacek Mańdziuk – Warsaw University of Technology
- prof. Anna Timofiejczuk- Silesian University of Technology
Description
This track is decicated for Businesss Pass participants and covers all aspects of Artificial Intelligence research reflected in business AI projects. Participants of this track are generally business representatives willing to share their perspective on theoretical and practical aspects of business AI projects realization.
For Business Pass holders, participation in the conference does not require paper submission, only a one-page summary of the project to be presented is expected.
AI in Human Behavior Analysis
Chairs
- prof. Katarzyna Harężlak- Silesian University of Technology
- prof. Pawel Kasprowski- Silesian University of Technology
- prof. Krzysztof Simiński – Silesian University of Technology
Description
The goal of this track is to explore the role of artificial intelligence in analyzing and interpreting human behavior across various domains, including psychology, healthcare, marketing, or social sciences.
The scope covers (but is not limited to) various aspects of behavior: human actions and psychological states, human gestures, movements, postures, activity patterns, and social interactions.
Decision-Making and Classification in Complex Systems
Chairs
- prof. Michał Baczyński – University of Silesia in Katowice
- prof. Piotr Porwik – University of Silesia in Katowice
- prof. Małgorzata Przybyła-Kasperek – University of Silesia in Katowice
Description
The track explores state-of-the-art methods, tools, and frameworks for decision-making and classification in systems characterized by high complexity, uncertainty, and dynamic behavior. This track aims to provide researchers and practitioners with insights into challenges in different domains through theoretical advancements and practical applications.
Remote Sensing and Satellite Data Analysis
Chairs
- prof. Jakub Nalepa – Silesian University of Technology
- prof. Przemysław Biecek – Warsaw University of Technology
- dr eng. Krzysztof Kotowski – KP Labs
Description
Recent advancements in remote sensing, Earth observation, in-orbit data analysis, AI, and edge computing are revolutionizing scientific and industrial applications by enabling real-time data processing in space. This technology supports environmental monitoring, precision agriculture, disaster detection, and anomaly identification from telemetry data. By integrating AI into space systems, raw data such as multi/hyperspectral images and telemetry can be processed onboard, accelerating insights, enhancing scalability, and enabling faster anomaly responses. Despite its potential, challenges like hardware limitations for in-orbit processing, limited labeled datasets, and assessing model performance without target data persist. This session welcomes all contributions related to all aspects of the analysis of satellite data of all modalities – both on board satellites and on the ground. Let’s get ready to take off together.