About the Journal
Advancing Intelligent Methods for Real-World Systems
JMIAS — Journal of Machine Intelligence and Applied Systems is an international peer-reviewed journal initiative of the Institute for Engineering and Scientific Advancement (IESA). The journal connects the development and evaluation of intelligent methods with the challenges of real-world systems.
JMIAS is in its founding stage. We are currently building the editorial team and reviewer community before opening manuscript submissions.
Aims & scope
The journal's intended scope includes original research and critical reviews that connect sound methodology, clear evidence, and practical relevance. Contributions may be theoretical, experimental, computational, or application-oriented.
- Machine learning and artificial intelligence: learning algorithms, neural models, reasoning, and predictive methods.
- Intelligent systems and automation: robotics, adaptive control, decision-making, and process automation.
- Data analytics and decision support: optimization, forecasting, data-driven discovery, and analytics.
- Vision and language technologies: computer vision, natural language processing, and multimodal systems.
- Connected and embedded systems: intelligent IoT, edge computing, sensing, and cyber-physical systems.
- Responsible and human-centred AI: explainability, reliability, ethical design, and human–AI interaction.
Join the editorial community
We invite expressions of interest from researchers and practitioners with relevant research expertise who would like to contribute to the founding editorial team or reviewer community.
Prospective editors
Help shape the journal's scholarly direction, editorial standards, and community. Please outline your research expertise, editorial or reviewing experience, and the contribution you would like to make.
Prospective reviewers
Contribute subject expertise and constructive assessment of research. Please describe your research topics, methods of expertise, and relevant publications or professional work.
How to express your interest
Email jmias@theiesa.org with the subject JMIAS Editorial Team Expression of Interest or JMIAS Reviewer Expression of Interest. Include your name, affiliation, areas of expertise, a short CV or a link to your ORCID or professional profile, and your preferred role. Please do not include unnecessary sensitive personal information.
Roles, responsibilities, and prospective appointments will be discussed with interested contributors. Expressing interest does not create an appointment or guarantee selection. Confirmed editorial appointments will be listed on the journal website.
Editorial vision & peer review
JMIAS aims to support rigorous editorial assessment, expert peer review, and constructive scholarly exchange. Assessment will focus on originality, technical quality, appropriate evaluation, transparency, clarity, and relevance to the journal's scope.
The peer review model, reviewer anonymity arrangements, and detailed procedures have not yet been finalized. These will be developed with the incoming editorial team and published before manuscript submissions open. No acceptance guarantee or fixed review time is offered.
Research integrity
The journal's intended standards include original work, accurate attribution, appropriate authorship, disclosure of competing interests and funding, and transparent reporting of methods and limitations. Authors will be expected to report applicable ethics approvals and permissions and disclose substantive use of generative AI tools. Detailed editorial policies will be finalized with the editorial team.
Launch information
Associated institution: Institute for Engineering and Scientific Advancement (IESA).
Current stage: recruitment of the founding editorial team and reviewers. Manuscript submissions are not yet open.
To be announced: confirmed editorial appointments, peer review model, publication frequency, licensing terms, publication charges, and the inaugural call for papers. ISSN, DOI registration, and indexing information have not yet been announced.
Questions and expressions of interest can be sent directly to jmias@theiesa.org.