The Journal of Big Data and Artificial Intelligence (JBDAI) (ISSN 2692-7977) is an open access peer-reviewed scholarly journal devoted to the publication of high-quality research on Artificial Intelligence (AI), big data, business analytics, informatics, data science, information systems, AI strategy, machine learning and related topics. JBDAI (formerly JBDTP) is the flagship journal of the New Jersey Big Data Alliance (NJBDA). The goal of this journal is to publish the latest contributions from academia, practitioners and industry to advance these fields. Original research papers, state-of-the-art reviews, innovative case studies and tutorials are invited for publication.

Areas of interest include:

• Artificial Intelligence (AI) - theory, applications, human interaction and impacts
• Big Data Theory and Foundational Issues
• Business Analytics
• Information systems and AI strategy
• Foundation Models / Large Language Models - theory, applications
• Data - Theory and Foundational Issues
• Data Mining Methods, Visualization
• Algorithms - Machine, Deep, Reinforcement Learning 
• Informatics, Knowledge Discovery Processes
• Intelligent Applications & Information Systems
• Ethical, policy and economic aspects of big data, machine learning and AI
• Big data analytics, data science and decision-making
• Interdisciplinary and multidisciplinary domain Applications of AI & big data (e.g. Finance, Policy, Healthcare, GIS, Business, Human Resources Physics, Supply Chain, Agriculture, Quant. Medicine, Ethics and more)
• Natural Language Processing, Understanding and Generation (NLP, NLU, NLG)

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