ICAML-2025.

Call for Paper

ICAML-2025 conference aims to provide a dynamic platform for researchers, academicians, and industry professionals to exchange innovative ideas, showcase cutting-edge developments, and discuss emerging trends in applied machine learning. ICAML-2025 is poised to foster interdisciplinary collaboration, driving advancements and inspiring impactful solutions in diverse domains of technology and science. ICAML-2025 invites original work from the following list of topics but is not limited to:

Track 1: Foundations of Machine Learning

• Supervised and Unsupervised Learning
• Reinforcement Learning and Multi-Agent Systems
• Deep Learning Architectures and Algorithms
• Feature Engineering and Data Preprocessing
• Probabilistic Models and Bayesian Inference
• Optimization Techniques in Machine Learning
• Interpretability and Explainable AI (XAI)
• Computational Complexity in Machine Learning

Track 2: Machine Learning in Industry and Business

• Predictive Analytics and Decision Support Systems
• Recommendation Systems and Personalization
• Fraud Detection and Risk Management
• Supply Chain Optimization and Demand Forecasting
• Customer Behavior Analysis and CRM Systems
• Chatbots and Conversational AI in Business
• Process Automation and Intelligent Systems
• AI in Marketing and Sales Optimization

Track 3: Machine Learning in Science and Engineering

• AI for Scientific Discovery and Simulation
• Machine Learning in Control Systems and Robotics
• Signal Processing and Pattern Recognition
• Computational Physics and Chemistry Applications
• Energy Systems and Smart Grid Analytics
• Environmental Modeling and Sustainability
• Biomedical Engineering and Diagnostics
• Materials Science and Computational Design

Track 4: Machine Learning for Social Good and Ethics

• AI for Healthcare and Public Health
• Education and Personalized Learning Systems
• AI for Smart Cities and Urban Planning
• Poverty Alleviation and Social Equity
• Disaster Management and Risk Assessment
• AI in Agriculture and Food Security
• Fairness, Accountability, and Ethical AI
• Legal and Policy Implications of Machine Learning

Track 5: Emerging Trends and Technologies

• Federated Learning and Edge Computing
• Quantum Machine Learning
• Neuromorphic Computing and Brain-Inspired AI
• Generative AI and Diffusion Models
• Meta-Learning and Lifelong Learning Systems
• AI for Internet of Things (IoT)
• Multimodal Machine Learning
• Transfer Learning and Domain Adaptation

Track 6: Machine Learning in Multimedia and Natural Interaction

• Natural Language Processing and Understanding
• Speech Recognition and Synthesis
• Image Processing and Computer Vision
• Augmented and Virtual Reality with AI
• Sentiment Analysis and Emotion Recognition
• Human-Computer Interaction with AI
• Video Analytics and Surveillance Systems
• AI for Gaming and Interactive Entertainment