Review of Artificial Intelligence
As an academic journal (quarterly), the journal of Review of Artificial Intelligence (RAI) adopts a two-way anonymous peer review mechanism to ensure the quality of articles.
This journal receives articles related to artificial intelligence research and especially welcomes the combination of industry applications. Topics of interest include, but are not limited to:
• Machine perception and multi-media sensing • Autonomous vehicles
• Intelligent and cooperative interacting robots
• Speech recognition and language use
• Cyber-physical systems, hybrid teams and Industry 4.0
• Knowledge representation
• Medical diagnosis and rehabilitation robots
• Process improvement and AI strategies for digital businesses
• AI in legal and Fintech industries
• Internet of Things
• Regulation and ethics
For articles with academic value, we are willing to provide multiple rounds of revision opportunities until the articles can be accepted. For all new submissions, the first round of review comments will be returned within 15 days, and all accepted articles will be published within one month.
We accept many types of paper:
Regular articles: These should describe new, carefully confirmed findings, innovative & creative research ideas and experimental procedures should be given in sufficient detail for others to verify the work. The length of a full paper should be the minimum required to describe and interpret the work clearly.
Research Articles: These should describe new, carefully confirmed findings, innovative & creative research ideas and experimental procedures should be given in sufficient detail for others to verify the work. The length of a full paper should be the minimum required to describe and interpret the work clearly. It also includes personalized review articles on the research work carried at the author(s)’ laboratory, based on the published work of the author(s).
Reviews Articles: Submissions of reviews and perspectives covering topics of current interest are welcome and encouraged. Reviews should be concise and no longer than 4-6 printed pages (about 12 to 18 manuscript pages). Review manuscripts are also peer-reviewed. It also focuses on current advancements in the given field.
Short communications: A short communication is suitable for recording the results of complete small investigations or giving details of new models or hypotheses, innovative methods, techniques, creative models etc., The style of main sections need not conform to that of full-length papers. Short communications are 2 to 4 printed pages (about 6 to 12 manuscript pages) in length. Reviews: Submissions of reviews and perspectives covering topics of current interest are welcome and encouraged. Reviews should be concise and no longer than 4-6 printed pages (about 12 to 18 manuscript pages). Review manuscripts are also peer-reviewed.
Reviewer/Advisory Editor :
- Wei Wang
Huazhong University of Science and Technology.Senior engineer.
- Xiaoliang Ma
Xidian University, Ph.D education background in Electronic Information Engineering. Prior to his Ph.D, he graduated from Oklahoma City University in 1999 with a master's degree in computational mathematics.
- Zhihao Xu
Qingdao University. He has PhD education background in computer and artificial intelligence. Main research interests: artificial intelligence, computer engineering, intelligent systems. He has published a number of scientific research papers, and has served as a reviewer for many well-known journals in the field of artificial intelligence.
- Yao Ni
Nankai University. He has a doctoral education background in Electronic Science and technology and his research interests are applied physics and micro nano electronic devices He have published more than 30 papers in concerned journals, such as nature communications, advanced materials, ACS Nano, nano energy, materials today physics, European Physical Journal Applied Physics, Acta physical Sinica, etc
- Qingyun Zeng
Dr. Zeng is a Research Scholar at the University of Pennsylvania specialized in mathematics and its applications in artificial intelligence, machine learning, and finance. His research interests include: differential geometry and topology, topological deep learning, computational geometry and machine perception, mathematical and statistical modelling in finance and economics. He got his PhD in mathematics from the University of Pennsylvania, fully supported by the Benjamin Franklin Fellowship. Before that, he studied pure mathematics at the University of Cambridge, fully supported by the Wing-Yip Cambridge Scholarship. He is also the Co-Founder and Vice President of Hunan Yunlu Hi-tech Co., Ltd.
- Meng Liu
Doctor of Computer Science and Technology, National University of Defense Science and Technology. His research focuses on Temporary Graph Learning, Deep Clustering. He has published several academic papers in top journals and academic conferences, and served as the reviewer of the Pattern Recognition, ESWA, FGCS and other journal conferences. He has won the third prize in the mathematics competition of the Chinese Mathematics Association.
- Tianxin Liang
He graduated from Renmin University of China with a Phd degree in computer application. He focuses on the research related to natural language processing (NLP) in the field of artificial intelligence (AI).
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