Generative AI: From Theory to Applications
A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Computing and Artificial Intelligence".
Deadline for manuscript submissions: 15 September 2026 | Viewed by 307
Special Issue Editors
Interests: generative AI; prompt engineering middleware; patterns; concurrency
Special Issue Information
Dear Colleagues,
Generative Artificial Intelligence (GenAI) has rapidly evolved from a primarily theoretical pursuit into a transformative technology with far-reaching scientific, industrial, and societal implications. Advances in foundation models, large language models (LLMs), diffusion models, multimodal generative systems, and agentic orchestration frameworks have redefined how we approach creativity, decision-making, scientific discovery, and human–machine interaction. At the same time, important theoretical and engineering questions remain regarding model generalization, interpretability, robustness, efficiency, and responsible deployment. Bridging theory and real-world applications is therefore both timely and essential to ensure that GenAI systems are reliable, ethical, and impactful.
We invite contributions to the Special Issue entitled “Generative AI: From Theory to Applications,” bringing together researchers and practitioners working across the GenAI spectrum—from foundational mathematical and algorithmic advances to innovative applications in science, engineering, healthcare, business, education, finance, and the creative industries. We particularly welcome submissions that connect theoretical insights to measurable improvements in deployed or practically relevant GenAI systems, supported by evaluation and clear methodological detail. Our goal is to foster interdisciplinary dialog and highlight emerging trends, challenges, and opportunities in this rapidly advancing field.
Suggested themes and article types for submissions:
In this Special Issue, original research articles and reviews are welcome. Research areas may include (but are not limited to) the following:
- Theoretical foundations of generative models, including probabilistic modeling, representation learning, scaling laws, generalization theory, and interpretability;
- Advances in generative architectures, such as LLMs, diffusion models, generative adversarial networks (GANs), multimodal and cross-modal systems, and efficient or domain-adaptive training methods;
- Applications of GenAI in domains including scientific discovery, healthcare, education, finance, cybersecurity, software engineering, and the creative industries;
- Responsible and trustworthy generative AI, including fairness, bias mitigation, robustness, privacy, security, governance, evaluation frameworks, and human-centered design.
We look forward to your contributions and to advancing the state of the art in generative AI.
Dr. Douglas C. Schmidt
Dr. Peng Zhang
Guest Editors
Manuscript Submission Information
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Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 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.
Keywords
- generative artificial intelligence
- large language models (LLMs)
- diffusion models
- generative adversarial networks (GANs)
- foundation models
- multimodal learning
- agentic orchestration frameworks
- AI ethics and responsible AI
- model interpretability and robustness
- AI applications in science and industry
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