International Conference on Artificial Intelligence and Application (ICAIA 2025)

The International Conference on Artificial Intelligence and Application (ICAIA 2025) explores the development and application of artificial intelligence techniques across various fields, including bioinformatics, machine learning, and intelligent systems.

Topics

• Algebraic Biology
• AI and Evolutionary Algorithms
• Applications in Bioinformatics
• Ant colony optimization
• Architectures of Intelligent Systems
• Approximate Reasoning
• Aspects of natural language processing
• Aspects of knowledge structures
• Automated problem solving
• Aspects of text technology
• Bioinformatics and computational biology
• Bayesian methods
• Biostatistics
• Biological network analysis
• Combining multiple knowledge sources in an integrated intelligent system
• Brain models / cognitive science
• Constraint-based reasoning and constraint programming
• Computational Science
• Data Mining
• Cross-Entropy method
• Constructions technology economy and management
• Decision support systems
• Data Sensing and Analysis
• Contracting and Legal Issues
• Distributed AI algorithms and Techniques
• Decision Support Systems
• Evaluation of AI tools
• Emerging Technologies
• Expert systems
• Evolutionary Computation
• Gaussian graphical models
• Fuzzy logic, modeling, control and soft computing
• Grammatical inference
• General issues in graph and tree mining
• Graph learning based on graph grammars
• Granular Computing
• Hierarchical learning models
• Heuristic optimization techniques
• Hybrid Intelligent Systems
• High-throughput data analysis
• Inductive learning and applications
• Image processing and understanding (interpretation)
• Integration of AI with other technologies
• Information-theoretical approaches to graphs
• Intelligent databases
• Intelligent agents
• Knowledge acquisition and discovery techniques
• Intelligent information fusion
• Knowledge-intensive problem solving techniques
• Knowledge networks and management
• Learning and adaptive sensor fusion
• Languages and programming techniques for AI
• Markov chain Monte Carlo (MCMC) methods
• Machine learning
• Motif search
• Meta learning
• Multiple hypothesis testing
• Multi-criteria reinforcement learning
• Natural language processing
• Multisensor data fusion using neural and fuzzy techniques
• Neural networks and applications
• Nature Inspired Methods
• Particle filter
• Real-world applications of Intelligent Systems
• Reinforcement learning
• Reasoning strategies
• Search and meta-heuristics
• Robotics
• Social intelligence (markets and computational societies)
• Simulated annealing
• Stochastic optimization
• Statistical learning theory
• Time series prediction
• Supervised and unsupervised classification of web data
• Unsupervised and Supervised Learning
• Topics on satisfiability
• Web Mining