Erudexa Publishing

International Comprehensive Technology and Science Journal aims to be a global home for work that advances technology and scientific understanding, with emphasis on reproducibility, rigorous evaluation, and ethical deployment. Topics include, but are not limited to:

• Foundational AI & machine learning theory, models and algorithms.
• Applied AI: computer vision, NLP, speech, recommender systems.
• Data science, big data analytics, and scalable data engineering.
• Software engineering for AI, model lifecycle management, MLOps.
• Robotics, autonomous systems, and sensor fusion.
• Cybersecurity, privacy-preserving ML, adversarial robustness.
• Edge/IoT computing, distributed systems, cloud-native architectures.
• Human–computer interaction, explainable AI, fairness, accountability and transparency in AI (FAT/ML).
• Datasets, benchmarks, reproducibility studies, and software/data papers.
• Interdisciplinary work linking computing with health, environment, education and society.

We particularly welcome reproducible submissions that include code, trained models or datasets with clear licensing and persistent identifiers.