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 (Institute of Science Tokyo);
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;
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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.

Selected Topics:

Selected Articles:

AI
“Explainable Artificial Intelligence (XAI): Concepts and Challenges in Healthcare”
by Tim Hulsen
AI 2023, 4(3), 652-666; https://doi.org/10.3390/ai4030034

MAKE
“XAIR: A Systematic Metareview of Explainable AI (XAI) Aligned to the Software Development Process”
by Tobias Clement, Nils Kemmerzell, Mohamed Abdelaal and Michael Amberg
Mach. Learn. Knowl. Extr. 2023, 5(1), 78-108; https://doi.org/10.3390/make5010006

MTI
“Designing Digital Escape Rooms with Generative AI in University Contexts: A Qualitative Study”
by Paula Rodríguez-Rivera, José M. Rodríguez-Ferrer and Ana Manzano-León
Multimodal Technol. Interact. 2025, 9(3), 20; https://doi.org/10.3390/mti9030020

Virtual Worlds
“Cybersickness in Virtual Reality: The Role of Individual Differences, Its Effects on Cognitive Functions and Motor Skills, and Intensity Differences during and after Immersion”
by Panagiotis Kourtesis, Agapi Papadopoulou and Petros Roussos
Virtual Worlds 2024, 3(1), 62-93; https://doi.org/10.3390/virtualworlds3010004

Big Data and Cognitive Computing
“GenAI Learning for Game Design: Both Prior Self-Transcendent Pursuit and Material Desire Contribute to a Positive Experience”
by Dongpeng Huang and James E. Katz
Big Data Cogn. Comput. 2025, 9(4), 78; https://doi.org/10.3390/bdcc9040078

Algorithms
“Review on Electrical Impedance Tomography: Artificial Intelligence Methods and its Applications”
by Talha Ali Khan and Sai Ho Ling
Algorithms 2019, 12(5), 88; https://doi.org/10.3390/a12050088

Computers
“The YOLO Framework: A Comprehensive Review of Evolution, Applications, and Benchmarks in Object Detection”
by Momina Liaqat Ali and Zhou Zhang
Computers 2024, 13(12), 336; https://doi.org/10.3390/computers13120336

Stats
“Estimation of Standard Error, Linking Error, and Total Error for Robust and Nonrobust Linking Methods in the Two-Parameter Logistic Model”
by Alexander Robitzsch
Stats 2024, 7(3), 592-612; https://doi.org/10.3390/stats7030036