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24 September 2025
MDPI’s Journal Cluster of Artificial Intelligence

Artificial intelligence (AI) was once a futuristic concept in science fiction stories but is now very tangibly integrated into modern society. AI is designed to perform tasks mimicking human intelligence, such as perception, recognition, and decision making. AI technology is advancing at a rapid pace, with new machine learning models capable of generating human speech, text, and images. AI has revolutionized the work, business, education, and research sectors, but its widespread utilization is not without risks and ethical dilemmas.

MDPI is expanding its portfolio towards relevant fields where research and discourse about artificial intelligence are topical and prevalent (e.g., AI in medicine). These new journals will complement the older journals, which are more generalized outlets for computer science research and broad AI research.

The member journals for this cluster are as follows:

AI (ISSN: 2673-2688) focuses on artificial intelligence (AI), including broad aspects of cognition and reasoning, perception and planning, machine learning, intelligent robotics, and applications of AI. AI is led by Editor-in-Chief Prof. Dr. Kenji Suzuki (Tokyo Institute of Technology);
AI in Medicine (ISSN: 3042-6707) focuses on the application of artificial intelligence and computer science techniques in medicine;
Algorithms (ISSN: 1999-4893) focuses on computer science, computational mathematics, artificial intelligence, automation and control systems, theory, methods and interdisciplinary applications, data and information systems, and software engineering. Algorithms is led by Editor-in-Chief Prof. Dr. Frank Werner (Otto-von-Guericke-University);
Big Data and Cognitive Computing (BDCC, ISSN: 2504-2289) is a scholarly online journal that provides a platform for big data theories with emerging technologies on smart clouds and for exploring supercomputers with new cognitive applications. It is a peer-reviewed, open access journal that publishes high-quality original articles, reviews, and short communications. BDCC is led by Editor-in-Chief Prof. Dr. Min Chen (South China University of Technology);
Machine Learning and Knowledge Extraction (MAKE, ISSN: 2504-4990) focuses on studies related to all areas of machine learning and knowledge extraction. MAKE is led by Editor-in-Chief Prof. Dr. Andreas Holzinger (University of Natural Resources and Life Sciences);
Multimodal Technologies and Interaction (MTI, ISSN: 2414-4088) focuses on presenting research that combines different types of input and output in ways that can enrich user experience, covering both fundamental and applied research dealing with the design, analysis, evaluation, and use of technologies that support multimodal interaction and their impact. MTI is led by Editors-in-Chief Prof. Dr. Mark Billinghurst and Prof. Dr. Cristina Portales;
Stats (ISSN: 2571-905X) is an international, peer-reviewed, open access journal on statistical science published quarterly online by MDPI. This journal focuses on methodological and theoretical papers in statistics, probability, stochastic processes, and innovative applications of statistics in all scientific disciplines including biological and biomedical sciences, medicine, business, economics and social sciences, physics, data science, and engineering. Stats is led by Editor-in-Chief Prof. Dr. Wei Zhu (State University of New York at Stony Brook, USA);
Virtual Worlds (ISSN: 2813-2084) focuses on Virtual Reality, Augmented and Mixed Reality technologies, and their uses. Virtual Worlds is led by Editor-in-Chief Prof. Dr. Anton Nijholt (University of Twente);
Computers (ISSN: 2073-431X) focuses on computer sciences, including computer and network architecture, computer–human interaction, and artificial intelligence. Computers is led by Editor-in-Chief Prof. Dr. Paolo Bellavista (University of Bologna).

Journals	Launch Year	Impact Factor (2024)	CiteScore (2024)	First Decision (median)	Acceptance to Publication (median)	APC (CHF)
	2020	5.0	6.9	20.7	3.9	1600
	Pending release	/	/	19	4	1000
	2008	2.1	4.5	17.8	3.6	1800
	2017	4.4	9.8	24.5	4.6	1800
	2017	6.0	9.9	25.5	3.4	1800
	2017	2.4	5.8	25	3.8	1800
	2018	1.0	1.8	18.2	2.9	1600
	2020	/	/	19.2	4.7	1000
	2012	4.2	7.5	16.3	3.8	1800

MDPI’s mission and values:

As a pioneer of academic open access publishing, MDPI has served the scientific community since 1996. We aim to foster scientific exchange in all forms across all disciplines. MDPI's guidelines for disseminating open science are based on the following values and guiding principles:

Open Access—All of our content is published in open access and distributed under a Creative Commons License, providing free access to science and the latest research, allowing articles to be freely shared and content to be re-used with proper attribution;
Timeliness and Efficiency—Publishing the latest research through thorough editorial work, ensuring a first decision is provided to authors in under 32 days and papers are published within 7-10 days upon acceptance;
Simplicity—Offering user-friendly tools and services in one place to enhance the efficiency of our editorial process;
High-Quality Service—Supporting scholars and their work by providing a range of options, such as journal publication at mdpi.com, early publication at preprints.org, and conferences on sciforum.net to positively impact research;
Flexibility—Adapting and developing new tools and services to meet the research community's changing needs, driven by feedback from authors, editors, and readers;
Rooted in Sustainability—Ensuring the long-term preservation of published papers and supporting the future of science through partnerships, sponsorships, and awards.

By adhering to these values and principles, MDPI remains committed to advancing scientific knowledge and promoting open science practices.

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