Journal Finder

Machine Learning: Engineering is a multidisciplinary open access journal dedicated to the application of machine learning (ML), artificial intelligence (AI) and data-driven computational methods across all areas of engineering. The journal also publishes research that presents methodological, theoretical, or conceptual advances in machine learning and AI with applications to engineering.

Technical areas concerned with smart materials and structures: Materials science: composites, ceramics, processing science, interface science, sensor/actuator materials, chiral materials, conducting and chiral polymers, electrochromic materials, liquid crystals, molecular-level smart materials, biomaterials. Sensing and actuation: electromagnetic, acoustic, chemical and mechanical sensing and actuation, single-measurand sensors, multiplexed multimeasurand distributed sensors and actuators, sensor/actuator signal processing, compatibility of sensors and actuators with conventional and advanced materials, smart sensors for materials and composites processing. Optics and electromagnetics: optical fibre technology, active and adaptive optical systems and components, tunable high-dielectric phase shifters, tunable surface control. Structures: smart skins for drag and turbulence control, other applications in aerospace/hydrospace structures, civil infrastructures, transportation vehicles, manufacturing equipment, repairability and maintainability. Control: structural acoustic control, distributed control, analogue and digital feedback control, real-time implementation, adaptive structure stability, damage implications for structural control. Information processing: neural networks, data processing, data visualization and reliability.