Tracks

TRACKS AND TRACK CHAIRS

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. Jerzy Stefanowski - Poznan University of Technology
• prof. Michał Woźniak - Wrocław University of Science and Technology
• prof. Ireneusz Czarnowski - Gdynia Maritime University

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.

• prof. Agnieszka Ławrynowicz - Poznan University of Technology
• prof. Dariusz Krol - Wrocław University of Science and Technology
• prof. Grzegorz J. Nalepa - Jagiellonian University

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 and machine learning are used in many medical applications: from molecular biology and drug design, digital pathology, diagnostic methods, planning therapies, and personalized management of mental disorders. In this track, we shall welcome all such applications, including identification of medical problems, data mining and big medical data analytics, biomedical signal and image processing, knowledge-based expert systems in biomedicine, natural language models, document classification and medical information retrieval, patient engagement support, ambient assisted living, telemedicine, and e-health, wearable sensors and trackers for healthcare, predictive data analytics and risk measures, and other relevant topics.

Neural Network and Deep Learning Systems

Chairs

• prof. Aleksander Byrski - AGH University of Science and Technology
• prof. Maria Ganzha - Warsaw University of Technology
• prof. Marcin Kurdziel - AGH University of Science and 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

• prof. Maciej Piasecki - Wrocław University of Science and Technology
• prof. Piotr Pęzik - University of  Lodz

Computer Vision

• prof. Leszek Chmielewski - Warsaw University of Life Sciences
• prof. Krzysztof Gajowniczek - Warsaw University of Life Sciences
• prof. Bogdan Kwolek - AGH University of Science and Technology

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

• prof. Beata Zielosko - University of Silesia in Katowice
• prof. Agnieszka Jastrzębska - Warsaw University of Technology
• dr Piotr Wasilewski - Systems Research Institute, Polish Academy of Sciences

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

• prof. Piotr Skrzypczyński - Poznan University of Technology
• prof. Piotr Lipiński - Lodz 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 2023 in the RAS track. 

Problem Solving and Optimisation

• 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

• prof. Dariusz Plewczyński - Warsaw University of Technology
• prof. Tomasz Gambin - Warsaw University of Technology
• prof. Robert Nowak - Warsaw University of Technology

Description

• prof. Maciej Zięba - Wroclaw University of Technology
• prof. Tomasz Trzciński - Warsaw University of Technology
• prof. Przemysław Spurek - Jagiellonian University

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
• mgr Mikołaj Małkiński - Warsaw University of Technology
• dr Adam Żychowski - Warsaw University of Technology

Description

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

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.