International Conference on Machine Learning and Artificial Intelligence Applications (MLAIA) aims to the promote the exchange of ideas in Machine Learning and Artificial Intelligence Applications. Authors are solicited to contribute to the conference by submitting articles that illustrate research results, projects, surveying works and industrial experiences that describe significant advances in the following areas but are not limited to:

Machine Learning

    Algorithms and Models
    Development of novel machine learning algorithms.
    Advances in supervised, unsupervised, and reinforcement learning models.
    Deep learning architectures and innovations.
    ML for Optical Data Analysis
    Transfer learning and domain adaptation techniques.
    Optimization and Training
    Optimization methods for machine learning.
    Efficient training strategies and scalability.
    Hyperparameter tuning and optimization.
    Regularization techniques and generalization.
    Applications and Case Studies
    Machine learning in healthcare: diagnostics, drug discovery, medical imaging.
    Natural language processing: text classification, sentiment analysis, machine translation.
    Computer vision: object detection, image segmentation, facial recognition.
    Ethics and Fairness
    Intelligent Fiber Systems.
    Fairness and bias in machine learning models.
    Ethical considerations in algorithm design and deployment.
    Transparency and interpretability of machine learning systems.
    Privacy-preserving machine learning.
    Theoretical Foundations
    Statistical learning theory.
    Probabilistic graphical models.
    Information theory and its applications in machine learning.
    Convergence analysis and theoretical guarantees.

Artificial Intelligence Applications

    Intelligent Systems and Agent
    Development of intelligent agents and autonomous systems.
    Multi-agent systems and cooperation.
    Robotics and AI integration.
    AI in Optical System Design and Optimization
    Human-agent interaction and collaboration.
    Knowledge Representation and Reasoning
    Knowledge graphs and semantic web.
    Logical reasoning and inference engines.
    Ontologies and knowledge bases.
    Commonsense reasoning and cognitive architectures.
    AI in healthcare 
    Intelligent diagnosis . 
    Clinical decision-making. 
    Intelligent medical devices and robots. 
    Medical big data and artificial intelligence technologies​ .  
    AI in Industry
    Quantum Photonics and AI
    AI-driven supply chain optimization.
    Intelligent manufacturing and Industry 4.0.
    AI in environmental monitoring and sustainability.
    AI in disaster response and humanitarian aid.
    AI and Human-Computer Interaction
    User interface design for AI systems.
    Voice assistants and natural language interfaces.
    Gesture recognition and multimodal interaction.
    Accessibility and AI for people with disabilities.
    Virtual and augmented reality applications. 
    Game development and Al.