STRATI Journal of Artificial Intelligence and Machine Learning

The journal aims to:

• Publish high-quality, original research that advances the theoretical foundations and practical implementations of AI and ML.
• Foster interdisciplinary dialogue between AI/ML and other scientific and engineering disciplines.
• Highlight innovative applications of AI and ML across diverse sectors including healthcare, finance, manufacturing, robotics, education, and governance.
• Encourage research that addresses ethical, social, and policy implications of AI and ML technologies.
• Support the development of algorithms, models, and systems that enhance automation, decision-making, and intelligent behavior.

The scope includes but is not limited to:

• Fundamental AI and ML theories, algorithms, and architectures.
• Deep learning, reinforcement learning, natural language processing, and computer vision.
• Explainable AI, interpretable models, and fairness in machine learning.
• AI-driven automation, robotics, and intelligent agents.
• AI and ML applications in real-world problems across industry, healthcare, education, and governance.
• Ethical, legal, and societal aspects of AI and ML deployment.
• AI hardware, optimization techniques, and computational efficiency.

Detailed Themes

The journal welcomes submissions on a wide range of themes, including but not limited to:

Core AI and ML Techniques

• Supervised, unsupervised, and semi-supervised learning
• Deep neural networks and architectures
• Reinforcement learning and multi-agent systems
• Evolutionary algorithms and swarm intelligence
• Probabilistic graphical models and Bayesian learning

Specialized AI Subfields

• Natural language processing and speech recognition
• Computer vision and image/video analysis
• Knowledge representation and reasoning
• Cognitive computing and AI neuroscience
• Human-AI interaction and collaborative intelligence

Applications and Case Studies

• AI in healthcare diagnostics, personalized medicine, and bioinformatics
• AI for finance, risk analysis, and fraud detection
• Intelligent robotics and autonomous systems
• Smart manufacturing, Industry 4.0, and predictive maintenance
• AI in education, e-learning, and adaptive tutoring systems
• AI for governance, public policy, and social good

Ethical, Legal, and Social Implications

• Fairness, accountability, and transparency in AI
• Privacy-preserving machine learning and data ethics
• AI policy frameworks and governance models
• Societal impact and responsible AI development

Emerging Trends and Technologies

• Explainable and interpretable AI models
• AI hardware accelerators and edge computing
• Quantum machine learning and hybrid systems
• AI for climate change, sustainability, and environmental monitoring

Send your paper to Email: strat.institute@gmail.com