Official Journal of ISQGD
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About the Journal — JAIDSEM

ISQGD Journal of Artificial Intelligence and Data Science in Engineering and Mathematics

Bridging Artificial Intelligence, Data Science, Engineering, and Mathematics

The ISQGD Journal of Artificial Intelligence and Data Science in Engineering and Mathematics is envisioned as a flagship interdisciplinary journal of ISQGD, dedicated to high-quality research at the intersection of artificial intelligence, data science, engineering, and mathematics.

The journal aims to provide an elegant, internationally visible platform for original research articles, survey papers, and interdisciplinary contributions that combine mathematical depth, engineering relevance, computational innovation, and real-world impact.

Publication Policy: All ISQGD journals currently operate under a fully supported publication model with no submission fees and no publication charges. This policy reflects ISQGD’s commitment to the free, equitable, and globally accessible dissemination of high-quality mathematical and interdisciplinary research.

Current Issue

The inaugural issue page below is presented as the first entry point for the journal and may be refined further as Volume 1 is finalized.

Current Publication

Volume 1 • Issue 1

Inaugural Issue — ISQGD Journal of Artificial Intelligence and Data Science in Engineering and Mathematics

The first issue is intended to establish the journal’s identity through carefully selected contributions in artificial intelligence, data science, engineering applications, mathematical foundations, and related interdisciplinary areas. It may include foundational articles, invited contributions, expository surveys, and original research papers.

Journal Character

This journal is designed to present artificial intelligence and data science in close dialogue with engineering and mathematics. Its visual identity follows the elegant ISQGD style while establishing a distinctive interdisciplinary and modern research profile.

The long-term goal is to develop a respected international journal marked by rigor, clarity, editorial care, and a strong thematic identity at the intersection of Artificial Intelligence, Data Science, Engineering, and Mathematics.

Journal Archive

All issues of the journal may be listed here as the publication develops, forming a permanent scholarly archive under ISQGD.

About the Journal

The journal is intended to serve as a research publication representing the academic vision of ISQGD, with emphasis on rigor, originality, structural understanding, engineering applications, and interdisciplinary relevance.

Purpose

The journal provides an official scholarly platform where substantial work in artificial intelligence, data science, engineering, and mathematics can be published under the institutional umbrella of ISQGD. It is meant to support a serious international research publication contributing to mathematical theory, engineering innovation, and modern computational science.

In its long-term vision, the journal may grow toward wider indexing, formal archival development, and increasing international participation from mathematicians, engineers, computer scientists, and interdisciplinary researchers.

Intended Readership

  • Researchers in artificial intelligence, machine learning, and data science
  • Mathematicians working in optimization, probability, geometry, topology, and dynamics
  • Engineers working in intelligent systems, robotics, design, and simulation
  • Data scientists and interdisciplinary computational researchers
  • Graduate students and advanced scholars entering these fields

Aims and Scope

The journal publishes high-quality research at the intersection of artificial intelligence, data science, engineering, and mathematics, with strong emphasis on mathematical foundations, innovative methods, computational techniques, and interdisciplinary applications.

Editorial Vision

This journal seeks to create a distinctive scholarly home for work that unites rigorous mathematical theory, data-driven methodology, engineering applications, and modern computational developments.

It particularly welcomes contributions that bring together abstraction, modeling, computation, and practical implementation in meaningful and original ways.

What the Journal Welcomes

  • Original research articles
  • Survey papers of lasting value
  • Interdisciplinary contributions connecting AI, data science, engineering, and mathematics
  • Expository articles accessible to a broad scholarly audience
  • Selected invited papers from special sessions or related scholarly activities

Topics Covered

The ISQGD Journal of Artificial Intelligence and Data Science in Engineering and Mathematics welcomes original research articles, survey papers, and interdisciplinary contributions in, but not limited to, the following areas:

1. Mathematical Foundations of AI and Data Science

  • Mathematical analysis of machine learning algorithms
  • Optimization theory (convex, non-convex, stochastic optimization)
  • Probability theory and stochastic processes
  • Statistical learning theory
  • Information theory and entropy methods
  • Functional analysis and operator theory in learning
  • Harmonic analysis and signal representations
  • Geometric and topological methods in data analysis
  • Graph theory and network science
  • Dynamical systems and learning dynamics

2. Artificial Intelligence and Machine Learning

  • Supervised, unsupervised, and reinforcement learning
  • Deep learning and neural network architectures
  • Explainable and interpretable AI
  • Generative models (GANs, diffusion models, VAEs)
  • Transfer learning and meta-learning
  • Federated and distributed learning
  • AI for scientific computing
  • Symbolic AI and hybrid models
  • AI ethics, fairness, and robustness

3. Data Science and Statistical Methods

  • Big data analytics and high-dimensional data analysis
  • Statistical inference and modeling
  • Bayesian methods and probabilistic programming
  • Time series analysis and forecasting
  • Data mining and pattern recognition
  • Dimensionality reduction and manifold learning
  • Computational statistics
  • Uncertainty quantification

4. Engineering Applications of AI and Data Science

  • Intelligent systems and automation
  • Signal and image processing
  • Computer vision and pattern analysis
  • Virtual reality applications and simulations
  • Control systems and robotics
  • Smart systems and IoT (Internet of Things)
  • Cyber-physical systems
  • AI in electrical, mechanical, civil, and industrial engineering
  • Engineering design optimization
  • AI in engineering design method
  • AI in human centered design

5. Computational and Numerical Methods

  • Numerical linear algebra
  • Scientific computing and simulation
  • Computational optimization
  • High-performance computing for AI
  • Sparse and low-rank methods
  • PDE-based models in data science
  • Computational geometry

6. Interdisciplinary and Emerging Areas

  • AI in physics, biology, medicine, and finance
  • Mathematical biology and bioinformatics
  • Quantum computing and quantum machine learning
  • Topological data analysis
  • Complex systems and network dynamics
  • Fractal geometry and multifractal analysis in data
  • AI for sustainability and climate science

7. Applications and Case Studies

  • Real-world applications of AI and data science
  • Industrial and technological innovations
  • Data-driven modeling and decision-making
  • Cross-disciplinary applications bridging mathematics, AI, and engineering

8. Expository and Survey Articles

  • High-quality survey papers on emerging topics
  • Mathematical and engineering perspectives on modern AI developments
  • Interdisciplinary expositions accessible to a broad audience

Closing Line

The journal particularly encourages contributions that bridge rigorous mathematical theory with engineering applications, fostering innovation at the intersection of Artificial Intelligence, Data Science, Engineering, and Mathematics.

Types of Contributions

The journal may include a carefully selected range of scholarly contributions, with emphasis on originality, depth, and interdisciplinary significance.

Research Articles

Original papers presenting new results, methods, theoretical developments, computational approaches, or engineering applications in artificial intelligence, data science, mathematics, or closely connected areas.

Survey and Expository Articles

High-level surveys or carefully written expository pieces that clarify important topics, methods, or emerging directions relevant to AI, data science, engineering, and mathematics.

Interdisciplinary Contributions

Papers that bridge traditional disciplinary boundaries and bring together mathematical theory, engineering applications, data-driven methods, and artificial intelligence in innovative ways.

Editorial Structure

The journal follows a streamlined and focused editorial structure to ensure efficiency, clarity, and strong academic oversight.

Editor-in-Chief

Provides overall academic leadership, defines editorial direction, ensures quality standards, and makes final decisions on all manuscripts.

Editorial Assistant

Assists with submissions, editorial correspondence, manuscript tracking, formatting, scheduling, and preparation of issues for publication. This is an administrative and operational role and may be voluntary or compensated depending on the needs of the journal.

Editors

Handle manuscript evaluation within their areas of expertise, support the review process, recommend decisions, and contribute to maintaining the academic quality of the journal.

Author Guidelines

The following points provide a clean initial framework for manuscript preparation and submission.

Submission Format

  • Initial submission should be a PDF file of the manuscript for screening and review
  • The PDF should be clear, complete, and formatted in a professional academic style
  • After acceptance, authors will be requested to submit the source file in the journal’s prescribed format
  • Authors should include title, abstract, author affiliation, and email address
  • References should be complete and consistently formatted

Writing Expectations

  • Results should be clearly stated and mathematically sound
  • Engineering and computational aspects should be presented with clarity where relevant
  • Notation should be readable and consistent
  • Abstracts should accurately reflect the content of the manuscript
  • Authors are responsible for originality and citation accuracy

Review and Publication Policy

All submitted manuscripts may undergo editorial screening and, where appropriate, expert review. The journal aims to maintain academic seriousness while developing a professional and efficient editorial process.

As the journal grows, its policies may be refined further to support regular publication, high editorial standards, and broader international recognition.

Call for Papers

The ISQGD Journal of Artificial Intelligence and Data Science in Engineering and Mathematics warmly invites submissions from the global research community. Authors working in areas aligned with the journal’s mission are encouraged to contribute original, rigorous, and well-prepared manuscripts.

For manuscript submission, editorial inquiries, or expressions of interest regarding the journal, please contact:

✉️ fvillecco@unisa.it

Suggested subject line: Submission for ISQGD Journal of Artificial Intelligence and Data Science in Engineering and Mathematics

To learn more about the International Society in Quantization, Geometry, and Dynamics, please visit:

🌍 https://www.isqgd.org/

Published by: International Society in Quantization, Geometry, and Dynamics (ISQGD)