Advances in Artificial Intelligence and Emerging Machine Learning Applications

Dear Colleagues,

This Special Issue, Advances in Artificial Intelligence and Emerging Machine Learning Applications, seeks to explore the latest advancements, methodologies, and real-world implementations of artificial intelligence (AI) and machine learning (ML). The primary focus is on novel algorithmic development, deep learning architectures, transformer and diffusion models, and their cross-disciplinary applications, particularly in domains such as computer vision, medical imaging, cybersecurity, and autonomous systems.

The scope includes both foundational research and applied innovations, emphasizing:

• Deep learning frameworks (CNNs, RNNs, transformers, diffusion models)
• Generative models and self-supervised learning
• Interdisciplinary applications in healthcare, remote sensing, IoT, smart cities, and bioinformatics
• Hybrid models integrating traditional ML with domain-specific knowledge
• Emerging areas such as explainable AI (XAI), responsible AI, and federated learning

The purpose is to provide a comprehensive platform for researchers and practitioners to share cutting-edge work that addresses current challenges and pushes the boundaries of what AI and ML can achieve in real-world contexts.

While numerous publications address AI and ML separately or in specific fields, this Special Issue uniquely integrates theoretical advances with application-driven insights. It bridges the gap between core algorithmic innovation and deployment in high-impact domains. By featuring interdisciplinary research and cross-domain experimentation, it aims to

• Highlight synergies between diverse AI techniques
• Offer comparative evaluations and benchmarks
• Address limitations of existing models through practical use cases
• Propose new directions for responsible and interpretable AI

This Special Issue will thus serve as a valuable supplement to the existing literature by broadening the lens through which AI research is disseminated and evaluated, especially with regard to its societal and technological impact.

Dr. Naveed Ilyas
Dr. Taqi Abrar
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. AI is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

• artificial intelligence
• machine learning
• deep learning
• transformer networks
• generative models
• computer vision
• medical image analysis
• explainable AI
• interdisciplinary applications
• diffusion models