[AISWorld] CFP: Journal of Big Data and Artificial Intelligence (JBDAI)

[Emre Yetgin]

Dear Fellow Researchers, Department Chairs, and Program Directors, 

We are excited to bring your attention to New Jersey Big Data Alliance <https://njbda.org/>’s (NJBDA) flagship journal, Journal of Big Data and Artificial Intelligence <https://jbdai.org/index.php/JBDAI> (JBDAI), backed by almost all universities in New Jersey, including numerous R1, R2 and other institutions such as Stevens, Rutgers, NJIT, Princeton, Montclair, Kean, NJCU, Rowan,WPU, TCNJ, Rider, and others. JBDAI is an open access peer-reviewed journal devoted to the publication of high-quality papers on theoretical and practical aspects of big data, AI, machine learning, NLP and associated topics. The goal of this journal is to publish the latest contributions from academia, practitioners and industry to advance thought leadership in these fields. Original research papers, state-of-the-art reviews, innovative case studies and tutorials are invited for publication.  JBDAI intends to publish one volume per year, and accepted articles will be published online on a continuous basis with rapid and rigorous publication cycles. JBDAI is sponsored by NJBDA and there are no publication costs or fees to publish or read published articles, thus enhancing their impact. 

Areas of interest include (but not restricted to):

• Artificial Intelligence 

• Data Science and Business Analytics

• Machine Learning

• Knowledge Discovery

• Ethical, policy and economic aspects of big data, machine learning and AI

• Big data analytics and decision-making

• Natural Language Processing (NLP) and text informatics

Our 2024 issue can be found on our website <https://jbdai.org/index.php/JBDAI>, and the 2025 issue is under production. Please encourage your faculty and doctoral students to consider submitting their works to JBDAI.  Instructions for submitting a manuscript can be found here <https://jbdai.org/index.php/JBDAI/about/submissions>. While JBDAI is not yet a top journal, it has tremendous potential and can serve as a strong and legitimate publication avenue for many of your faculty colleagues and doctoral students. We are not only looking for submissions of scholarly articles but also for established NJ scholars to join our review panel and help advance scholarship in big data, informatics, data science and AI. 

Please feel free to contact us at editor at jbdtp.org <mailto:editor at jbdtp.org> if you or any of your faculty have questions.

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Emre Yetgin, Ph.D.
Associate Professor, Department of Information Systems, Analytics, and Supply Chain Management
Director, Center for Business Analytics
Sweigart Hall 367
Norm Brodsky College of Business, Rider University
2083 Lawrenceville Rd., Lawrenceville, NJ 08648