Rough Sets were introduced by Zdzisław Pawlak in the early '80s and developed further as a method of knowledge representation and processing based on uncertain data and incomplete information. Nowadays, Rough Set theory is widely recognized to have great importance in several fields, including artificial intelligence, mathematics, knowledge representation and machine learning, as evidenced by the increasing number of works concerned with its applications and theoretical foundations.

The 2024 International Joint Conference on Rough Sets (IJCRS 2024) will take place in Halifax (Canada) from May 17 to May 20, 2024, and will be hosted by the MSc in Computing and Data Analytics (MCDA) program at Saint Mary's University, Halifax. IJCRS is the principal international conference sponsored by the International Rough Set Society (IRSS).

The IJCRS conference aims to be the main location for disseminating novel foundational results and practical applications, enabling the discussion of problems and exchange of ideas, as well as bringing together academic and industrial perspectives, centred around rough sets and related disciplines (such as granular computing, three-way decisions and fuzzy sets).

We invite submissions of original and previously unpublished research on rough set theory, including but not limited to the following topics:

Core Rough Set Models And Methods: Covering/Neighborhood-based rough set models; Decision-theoretic rough set models; Dominance-based rough set models; Game-theoretic rough set models; Logic in rough set models; Partial rough set models; Rough-Bayesian models; Rough clustering; Rough computing; Rough mereology; Rough-set-based feature selection; Rule-based systems; Variable precision rough set models

Related Methods And Hybridization: Anomaly, outlier, and novelty detection; Decision support systems; Dempster-Shafer theory; Formal concept analysis; Fuzzy sets; Fuzzy rough sets and rough fuzzy sets; Granular computing; Intelligent agent models; Interval computations; Nature-inspired computation models; Petri nets; Rough sets in data science, artificial intelligence, and machine learning; Three-way decision; Three-way data analytics; Topology and matroids; Uncertain and approximate reasoning; Uncertainty theory

Areas Of Applications: Astronomy and atmospheric sciences; Big data analytics; Bioinformatics; Business intelligence and business data analytics; Computer vision and image processing; Cybernetics and robotics; Financial markets; Interactive computing; Knowledge discovery; Knowledge engineering and representation; Medicine and health; Natural language processing; Retail and E-commerce; Risk monitoring; Semantic web; Smart cities; Telecommunications; Transportation; Web mining and text mining