Deadline Date: 30 January 2026
Introduction and Background
Artificial Intelligence (AI) and Machine Learning (ML) have revolutionized problem-solving across disciplines by offering advanced tools for automation, prediction, optimization, and decision support. In engineering and software development, AI-driven approaches are reshaping how we design, simulate, and validate complex systems. Simultaneously, the adoption of AI in fields like education, healthcare, finance, and cybersecurity underscores its broad social impact and growing necessity for responsible deployment.
As AI systems become increasingly embedded in critical infrastructures and workflows, challenges around interpretability, reliability, adaptability, and human trust become central to their successful application. The integration of AI into numerical methods, computational models, and software systems calls for new research that bridges theoretical development with practical needs - precisely the mission of RIMNI.
Aim and Scope of the Special Issue
This Special Issue aims to bring together cutting-edge research on the development, analysis, and application of AI and ML techniques across both traditional engineering domains and emerging interdisciplinary contexts. We particularly encourage submissions that highlight numerical methods, computational modeling, and software innovations enriched by AI.
In line with RIMNI's mission, the issue seeks to:
Explore how AI and ML are advancing engineering, and simulation.
Showcase AI applications in software engineering, especially those involving automation, defect detection, and predictive modeling etc.
Present cross-domain applications of AI (e.g., in education, health, security) where computational rigor and system reliability are critical
Address evaluation, ethics, and human-centered design of AI tools, particularly in high-stakes or regulated environments
Suggested Themes
We invite original research articles, reviews, and case studies on topics including (but not limited to):
AI-enhanced numerical methods for simulation, modeling, and optimization.
Integration of ML into engineering, software and mathematics.
Data-driven modeling and soft computing for system analysis and control.
AI for software analytics, automated testing, and intelligent development.
NLP and ML applications in software engineering and requirements processing.
AI for healthcare diagnostics, and educational personalization,
Explainability, robustness, and fairness in AI-driven systems.
Human-AI interaction and cognitive design in engineering and decision-making tools.
Numerical rigor with AI adaptability.
Evaluation frameworks and performance benchmarks for AI in engineering and social domains.
……
RIMNI-The journal's scope includes Computational and Numerical Models of Engineering Problems, Development and Application of Numerical Methods, Advances in Software, Computer Design Innovations, Soft Computing, Machine Learning, Artificial Intelligence, etc.
Artificial Intelligence (AI) and Machine Learning (ML) have revolutionized problem-solving across disciplines by offering advanced tools for automation, prediction, optimization, and decision support. In engineering and software development, AI-driven approaches are reshaping how we design, simulate, and validate complex systems. Simultaneously, the adoption of AI in fields like education, healthcare, ... show more
Editorial board
