Emerging Trends in Machine Learning and Artificial Intelligence

Dear Colleagues,

Machine learning (ML) and artificial intelligence (AI) are rapidly evolving fields that are fundamentally transforming various industries, such as healthcare, finance, agriculture, manufacturing, and education. Traditional approaches to AI and ML have been highly effective, but the ongoing advancements in these areas have led to the emergence of novel trends that push the boundaries of what is possible. These emerging trends are not only enhancing the performance and capabilities of AI systems but are also addressing some of the long-standing challenges in the field. Emerging AI and ML trends enhance image analysis, content creation, language processing, and real-time decision-making across diverse application areas like precision agriculture, emotion recognition, and autonomous systems. In specific, generative AI revolutionizes image, audio, video, and text applications. Despite these advancements, challenges remain. Hence, this Special Issue aims to address these challenges by disseminating recent advances in emerging AI and ML trends. It will focus on the flexibility and adaptability of these new approaches, as well as their potential to surpass traditional methods in terms of their performance. Original contributions as well as benchmarking studies with balanced literature reviews and engineering applications in emerging topics in AI and ML are welcome. Topics of interest for this Special Issue include, but are not limited to: 

• Generative AI and its applications;
• AI in healthcare;
• Multi-modal AI;
• AI and quantum computing;
• Federated learning and privacy-preserving AI;
• Large language models (LLMs) and their applications;
• Edge AI and TinyML;
• AI-enhanced cybersecurity;
• New trends in learning algorithms: self-supervised, active, contrastive, and continual learning;
• Graph neural networks and their applications;
• Ethics and responsible AI;
• Engineering applications of emerging AI and ML methods in biomedical, precision agriculture, affective computing, etc.

Dr. Thuseethan Selvarajah
Guest Editor

Manuscript Submission Information

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• artificial intelligence
• machine learning
• deep learning
• neural networks
• generative artificial intelligence
• natural language processing
• computer vision
• large language models
• reinforcement learning
• learning algorithms