Tracks and track chairs
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 leaning models.
Knowledge Engineering
Chairs
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.
dr
Marian Bubak
Sano Centre for Computational Medicine, AGH and ACC Cyfronet, Kraków.
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.
Marcin Kurdziel
AGH University of Science and Technology
Natural Language Processing, Automatic Speech Recognition, and Conversational AI
Chairs
prof.
Maciej Piasecki
Wrocław University of Science and Technology
prof.
Agnieszka Mykowiecka
Institute of Computer Science, Polish Academy of Sciences, Warsaw
prof.
Piotr Pęzik
University of Lodz
Computer Vision
Chairs
prof.
Leszek Chmielewski
Warsaw University of Life Sciences
.
prof.
Krzysztof Gajowniczek
Warsaw University of Life Sciences
Description
The session is organized in cooperation with the Institute of Information Technology, Warsaw University of Life Sciences – SGGW, the Association for Image Processing, Poland – Towarzystwo Przetwarzania Obrazów and the Section of Multimedia, Committee on Informatics of the Polish Academy of Sciences.
UNCERTAINTY IN ARTIFICIAL INTELLIGENCE
Chairs
prof.
Dominik Ślęzak
QED Software & University of Warsaw
.
prof.
Beata Zielosko
University of Silesia in Katowice
.
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
Chairs
prof.
Piotr Skrzypczyński
Poznan University of Technology
.
prof.
Piotr Lipiński
Lodz 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
Chairs
prof.
Jarek Arabas
Warsaw University of Technology
prof.
Karol Opara
Systems Research Institute, Polish Academy of Sciences
prof.
Robert Nowak
Warsaw University of 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.
Young.AI
(session for young researchers)
Chairs
dr
Arkadiusz Tomczyk
Lodz University of Technology
dr
Jakub Walczak
Lodz University of Technology
mgr
Stanisław Kaźmierczak
Warsaw University of Technology
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.
Interdisciplinary Applications of Artificial Intelligence (session for business and interdisciplinary researchers)
Chairs
prof.
Jacek Mańdziuk
Warsaw University of Technology
prof.
Adam Wojciechowski
Lodz University of Technology
prof.
Jarosław Wąs
AGH University of Science and Technology
prof.
Agnieszka Ławrynowicz
Poznań University of Technology
Description
The “Interdisciplinary Applications of Artificial Intelligence” track is a response to the ever-growing applications of artificial intelligence in interdisciplinary scientific and industrial research. The beneficiaries of artificial intelligence are both scientists, companies, institutions, and indirectly a human society benefiting from the contemporary achievements of science, including AI.
The invitation is addressed to both academia (academic pass) and companies and institutions (business pass) that interdisciplinarily implement artificial intelligence techniques and methods in various projects.
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;
An additional value will be the presentation of the results of scientific and research projects, which, in addition to its popularisation value, will provide a valuable source of inspiration for the academic community.