Call for Papers
Multi-scale Artificial Intelligence (MAI) refers to an approach in artificial intelligence that involves the integration of models and techniques across multiple scales. This approach enables AI systems to handle and analyze data at different levels of detail and resolution, from the microscopic to the macroscopic.
By using multi-scale representations, MAI can capture information at various levels of granularity, allowing for more comprehensive and accurate analysis. This technique is especially useful in fields like computer vision, where it can help in tasks such as image recognition, object detection, and scene understanding.
In essence, MAI combines the strengths of different AI techniques and models to work together at multiple scales, providing a more comprehensive understanding of complex systems and data. This approach can enhance the performance and accuracy of AI systems in various applications.
MAI 2026 welcomes submissions reporting research that advances artificial intelligence, broadly conceived. Original papers are invited to submit to the following Track areas:
| Track 1: Foundations of Artificial Intelligence |
Machine Learning, Natural Language Processing, Large Language Models, Neural Networks and Deep Learning, Computer Vision, Data Mining, Deep Learning Architectures (Transformers/CNNs/RNNs Evolution), Reinforcement Learning & Multi-agent Systems, Explainable & trustworthy AI, Federated & Distributed Learning, Neuro-symbolic Hybrid Systems, Meta-learning & Adaptive Algorithms, Graph Neural Networks & Knowledge Representation, Online & Continual Learning, Multimodal Fusion Techniques, Causal Reasoning & Logical Learning, Multiagent Systems, Knowledge Representation, Human-in-the-loop AI, Robotics and Perception |
| Track 2: Applications of Artificial Intelligence |
AI Applications in Healthcare and Medicine, AI Applications in Education, AI Applications in Finance, AI Applications in Smart Cities and Transportation, AI Applications in Aerospace, AI Applications in Engineering and Manufacturing, AI Applications in Business Intelligence, AI in Robotics and Autonomous Systems, AI in Smart Cities and Urban Computing, AI for Internet of Things, AI in Education and E-learning |
| Track 3: Multi-scale Artificial Intelligence and Applications |
Multi-scale Representation Learning in Artificial Intelligence, Multi-scale Object Detection and Recognition in Computer Vision, Multi-scale Artificial Intelligence for Big Data Analysis, Multi-scale Artificial Intelligence in Healthcare, Multi-scale Artificial Intelligence for Smart Cities, Scalable Machine Learning Techniques for Multi-scale Data Analysis, Cross-scale AI in Decision Support Systems |
| Track 4: Societal Impact & Emerging Frontiers |
AI ethics & governance frameworks, Privacy-preserving machine learning, Digital content authentication, Human-AI collaboration & cognitive augmentation, Brain-computer interfaces & neuro-AI, Affective computing & mental health, AI-assisted scientific discovery, Sustainable AI (green computing/carbon footprint), AI policy & legal studies, Virtual human technologies, Multimodal human-computer interaction, AI for art & creative generation, Open-source ecosystems & toolchains, AI education & talent development
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GUIDE FOR SUBMISSIONS:
*Papers prepared in the prescribed format are to be submitted. The papers should be written in English and clearly state the title, objective, method, results, and conclusion with major keywords. All papers submitted will be checked for plagiarism.
*Author names and their affiliations should be removed from the initial PDF file for the double blind review process. After receiving, the full paper will be peer-reviewed and its acceptance will be notified. Only papers presenting original content with novel research results or successful innovative applications will be considered for publication in the conference proceedings.
*The paper should be original work of the author(s), and no portion of the paper (including, but not limited to, graphics and figures) has been previously published. The paper is not currently under consideration for publication elsewhere.
*The authors listed on the paper accurately reflect those who actually did the work and contributed to the paper in a meaningful way, and they have identified and acknowledged all sources used in the creation of their paper or manuscript, including any graphics, images, tables, and figures.
PLAGIARISM POLICY:
*The paper prior to submission should be checked for plagiarism from licensed plagiarism tools like Turnitin or CrossCheck. The similarity content should not exceed 25% (in any case either self contents or others).
*Any form of self-plagiarism or plagiarism from others' works should not be there in a paper. If any model / concept / figure / table / data / conclusive comment by any previously published work is used in your paper, you should properly cite a reference to the original work.
