Special Issue "Future Trends of Artificial Intelligence (AI) and Big Data"

Dear Colleagues,

Recent advances in artificial intelligence (AI) and big data have dramatically changed the way we handle and analyze information. These technologies have become vital in several fields, including healthcare, security, education, media, and entertainment. The application of AI and big data has enabled us to accomplish tasks that were previously impossible, such as identifying complex patterns and trends, predicting outcomes, and automating decision-making processes.

This Special Issue aims to investigate the future trends of AI and big data, as well as their influence on various domains. Extended reality, art and culture, multimodal analysis, and multimedia retrieval are just a few of the areas that will be explored. We welcome original research papers and review articles that delve into topics such as edge computing, personalized medicine, ethics and the responsible use of AI, and natural language understanding, among others. We encourage researchers, scholars, and practitioners to submit their contributions and share their insights to enhance our understanding of the impact of AI and big data on society.

Topics of interest include, but are not limited to, the following:

• Emerging trends in AI and big data research;
• Applications of AI and big data in Industry 4.0;
• The ethics of AI and big data;
• Human–AI interaction and collaboration;
• Explainable AI and interpretability;
• Natural language processing and generation;
• Machine learning algorithms and techniques;
• Computer vision and image analysis;
• Big data analytics and visualization;
• Cloud computing and distributed systems for big data;
• Edge computing and AI at the edge;
• Social media analysis and sentiment analysis;
• Recommender systems and personalized recommendations;
• Deep learning and neural networks;
• Generative models and adversarial learning;
• AI and big data in education and e-learning;
• AR/VR and extended reality;
• AI and art/culture;
• AI and big data in environmental sustainability and climate change research;
• Impact of AI and big data on urban planning and smart cities;
• AI and big data for enhancing cybersecurity and data privacy.

Dr. Sotiris Diplaris
Dr. Stefanos Vrochidis
Dr. Ioannis Yiannis Kompatsiaris
Dr. Giuseppe Amato
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. Electronics is an international peer-reviewed open access semimonthly 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 2000 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.

• emerging trends in AI and big data research
• applications of AI and big data in Industry 4.0
• the ethics of AI and big data
• human–AI interaction and collaboration
• explainable AI and interpretability
• natural language processing and generation
• machine learning algorithms and techniques
• computer vision and image analysis
• big data analytics and visualization
• cloud computing and distributed systems for big data
• edge computing and AI at the edge
• social media analysis and sentiment analysis
• recommender systems and personalized recommendations
• deep learning and neural networks
• generative models and adversarial learning
• AI and big data on education and e-learning
• AR/VR and extended reality
• AI and art/culture
• AI and big data in environmental sustainability and climate change research
• impact of AI and big data on urban planning and smart cities
• AI and big data for enhancing cybersecurity and data privacy