About the Journal

AI Innovations and Applications is a globally distributed, open-access English-language academic journal dedicated to advancing cutting-edge theoretical exploration and practical innovation in artificial intelligence. The journal focuses on AI’s transformative applications, technological breakthroughs, and ethical/societal impacts, encouraging interdisciplinary research to serve as a high-quality, diverse platform for scholars, policymakers, and industry practitioners worldwide. 

(1) Core Research Areas

The journal covers (but is not limited to):

AI Foundations: Machine learning, deep learning, natural language processing, computer vision, knowledge graphs, and other theoretical advancements.

AI Applications: Healthcare, fintech, transportation, education, agriculture, industrial manufacturing, smart homes, and other industry-driven innovations.

Emerging Interdisciplinary Fields: AI integration with biology, physics, sociology, law, etc., exploring novel solutions to complex scientific and societal challenges.

(2) Key Features

Academic Rigor: Rigorous peer review ensures originality, theoretical depth, and practical relevance.

Open Science: Open-access model enables immediate global dissemination, maximizing research impact.

Global Perspective: A distinguished international editorial board fosters cross-cultural academic dialogue.

Practice-Oriented: Prioritizing case studies and empirical research to address real-world problems.

Submission Scope

(1) Article Types

Original research papers, reviews, short commentaries, and policy analyses are welcome. Priority given to data-driven studies, interdisciplinary research, emerging AI challenges

Topics of Interest (Including but Not Limited to)

AI Theory & Algorithms: Novel ML algorithms, deep learning architectures, reinforcement learning, optimization methods.

AI Applications: Medical diagnostics, financial risk prediction, smart traffic systems, AI in education/manufacturing.

Interdisciplinary Research: Bioinformatics, computational physics, social computing, AI-powered legal systems.

Ethics & Society: AI ethics, privacy, algorithmic bias, fairness, labor market impacts.

AI Systems: AI chips, cloud/edge computing, robotics, smart sensors.