Aims and Scope

Aims and Scope

The International Journal of Computational Intelligence in Engineering (IJCIE) (Online ISSN 3139-6852) is a peer-reviewed, fully open access journal published by DeepCognix AI Labs, Bangalore, India. IJCIE publishes original research, review articles, technical notes and case studies that advance the theory and the engineering practice of computational intelligence.

Aims

  • To provide a rigorously reviewed, freely accessible venue for research at the intersection of artificial intelligence and engineering.
  • To encourage work that is reproducible, methodologically sound and honestly reported, including negative and confirmatory results.
  • To shorten the distance between algorithmic research and deployable engineering systems.
  • To support researchers from all regions and career stages through transparent editorial practice and an affordable publishing model.

Scope

IJCIE welcomes submissions in, but not limited to, the following areas:

  • Machine learning and deep learning: supervised, unsupervised, self-supervised and reinforcement learning; neural architectures; transfer learning; federated and distributed learning; model compression and edge deployment.
  • Computational intelligence: fuzzy systems, evolutionary computation, swarm intelligence, metaheuristic and hybrid optimisation, granular and neuro-fuzzy computing.
  • Perception and language: computer vision, image and video analysis, speech and audio processing, natural language processing, multimodal learning.
  • Data science and analytics: time-series modelling, anomaly detection, predictive maintenance, big data pipelines, knowledge graphs.
  • Intelligent systems engineering: robotics, intelligent control, autonomous systems, cyber-physical systems, Internet of Things, edge and cloud computing.
  • Domain applications: intelligent methods applied to electrical, electronics, mechanical, civil, biomedical, environmental, materials and computer engineering, including healthcare informatics, power and energy systems, smart manufacturing, transportation and agriculture.
  • Trustworthy AI: explainability, fairness, robustness, privacy-preserving learning, security of machine learning systems, and the responsible use of AI in engineering practice.

What we expect from a submission

Manuscripts should state a clear problem, describe the method in enough detail to be reproduced, compare against relevant baselines on identified datasets, and report results with appropriate evaluation metrics. Claims must be supported by the evidence presented. Papers that repackage a standard method on a standard dataset without new insight, and papers outside the scope defined above, are declined without external review.

Article types

  • Original research articles presenting new methods, systems or empirical findings.
  • Review articles offering a critical, structured synthesis of a research area.
  • Technical notes and short communications reporting a focused result, dataset or tool.
  • Case studies documenting the engineering deployment of intelligent methods, including the practical constraints encountered.

Minimum manuscript length is 6 pages in the IJCIE template. There is no upper limit, provided the length is justified by the technical content.