Contributed papers are solicited describing original works in Algorithms, Data Mining, and Information Technology. Topics and technical areas of interest include but are not limited to the following:

Track 1: Algorithm Design and Analysis	Track 2: Data Mining and Knowledge Discovery	Track 3: Machine Learning and Artificial Intelligence
Graph and combinatorial algorithms	Association rule mining and pattern discovery	Deep learning architectures (CNNs, RNNs, Transformers)
Approximation, randomized, and parameterized algorithms	Clustering, classification, and regression methods	Reinforcement learning and transfer learning
Online and streaming algorithms	Sequential and temporal data mining	Generative models and representation learning
Algorithmic game theory and mechanism design	Graph mining and social network analysis	Explainable and fair machine learning
Optimization algorithms (convex, metaheuristic, nature-inspired)	Text mining, web mining, and information retrieval	Few-shot, zero-shot, and federated learning
Parallel, distributed, and quantum algorithms	Anomaly detection and outlier analysis	AI for data mining and big data analytics
Track 4: Information Systems and Big Data Technologies	Track 5: Applications and Emerging IT Trends
Big data storage, processing, and querying (Hadoop, Spark, Flink)	Recommendation systems and personalization
Data integration, cleaning, and quality management	Social media analytics and sentiment analysis
Distributed databases and NoSQL systems	Bioinformatics, healthcare, and biomedical data mining
Cloud and edge computing for information systems	Financial data analysis and fraud detection
Data lakes, data warehouses, and data governance	Cybersecurity, privacy-preserving data mining
High-performance computing and data-intensive applications	IoT data analytics and smart city applications