APL Machine Learning (AML)

APL Machine Learning is an international peer-reviewed open-access journal published by AIP Publishing that focuses on the rapidly growing intersection of machine learning, artificial intelligence, and scientific research. The journal provides a platform for researchers developing and applying machine learning methods in physics, materials science, engineering, chemistry, biology, and related disciplines. The journal publishes original research articles, reviews, and technical studies covering machine learning algorithms, artificial intelligence methods, data-driven modeling, scientific computing, neural networks, deep learning, and emerging AI technologies. It also highlights research where scientific knowledge contributes to the development of new machine learning systems, including advanced materials, devices, hardware architectures, and intelligent technologies. APL Machine Learning aims to connect two major research communities: scientists using ML approaches to accelerate discovery and researchers creating new AI concepts inspired by physical sciences. Topics include automated discovery, computational materials science, AI hardware, neuromorphic computing, predictive modeling, and data-driven engineering solutions.

APL Machine Learning (AML) is :-

• International, Peer-Reviewed, Open Access, Refereed, Machine Learning, Artificial Intelligence, Computer Science, Data Science, Computational Physics, Materials Science, Engineering Applications, machine learning algorithms, artificial intelligence methods, data-driven modeling, scientific computing, neural networks, deep learning, emerging AI technologies, advanced materials, devices, hardware architectures, intelligent technologies , Online , Quarterly Journal

• UGC Approved, ISSN Approved: P-ISSN E-ISSN: 2770-9019, Established: 2023,
• Does Not Provide Crossref DOI

• Not indexed in Scopus, WoS, DOAJ, PubMed, UGC CARE