Artificial Intelligence and Machine Learning Techniques for Mathematical Problem Solving

Dear Colleagues,

The remarkable growth of artificial intelligence (AI) and machine learning (ML) in recent years has led to innovative methodologies that are transforming conventional processes across various disciplines, including mathematical problem solving. The development and application of these sophisticated computational models have increasingly become critical for the modern scientific community.

This Special Issue aims to record the latest research, investigations, and innovations that utilize AI and ML techniques to resolve intricate mathematical challenges. It seeks to provide a comprehensive account for scholars, researchers, and experts to share their novel findings and further propagate the dynamic potential of AI and ML in mathematical problem solving. Furthermore, this Issue is placed within the broader scope of the journal, aligning with its commitment to promoting insightful advancements in mathematics and logic, and highlighting the potential applications of these fields.

We invite you to submit original research articles and reviews exploring diverse themes related to AI and ML applications in mathematical problem solving. Although the research topics are not limited, we particularly welcome papers that explore the role and influence of AI and ML in the following areas:

• Computer Vision: exploiting AI and ML techniques that automate the visual information flow while solving mathematical problems therein;
• Natural Language Processing: the use of AI and ML to comprehend, analyze, and decipher language-based data and address associated mathematical challenges;
• Bioinformatics: utilizing AI and ML for the mathematical analysis of complex biological data, including genetics, genomics, and proteomics;
• Control Systems: advancements in the use of AI and ML to enhance the efficiency and functionality of control systems;
• Smart Grid Systems: the application of AI and ML in mathematical problem solving related to smart grid systems, including optimization and control, forecasting, security, and reliability;
• Security: utilizing AI and ML techniques for enhancing the security and resilience of mathematical systems and algorithms against potential threats and attacks.

We eagerly anticipate your valuable contributions to this Special Issue and look forward to the advancements that your research will bring to this dynamic field of study.

Dr. Minhyeok Lee
Dr. Yoojoong Kim
Prof. Dr. Gustavo Olague
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. Axioms 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 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.

• artificial intelligence
• machine learning
• deep learning
• computational models
• computer vision
• natural language processing
• bioinformatics
• control systems
• smart grid systems
• security