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ICAIM 2027: International Conference on Artificial Intelligence & Materials

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Submission Date:
2027-01-10 Due in 115 days
Notification Date:
2027-02-20
Conference Date:
2027-03-12
Location:
Changsha, China
Years:
Viewed: 5862   Tracked: 0   Attend: 0

Conference Partner Index (CP-I)

44.3 / 100
Ranked #3,094 of 5,682 conferences · Top 55%

#83 of 260 in Materials, Mechanical & Manufacturing #362 of 739 in Artificial Intelligence & Machine Learning

Academic recognition (35%) No data - scored at the neutral baseline of 50 —
Submission selectivity (20%) No data - scored at the neutral baseline of 50 —
Editions held (20%)
37
Community attention (10%)
10
Public record completeness (15%)
55

Inputs used: Editions on record: 3 · Researchers who opened this page in the past 24 months: 3

Missing from the public record: Historical acceptance rates (+4.5) · Best-paper records (+2.3)
Organizers can add these from this page after claiming the conference; scores are recomputed nightly. How to raise this score

Confidence 45% - the share of the score backed by observed data rather than the neutral baseline. How this score is calculated · Browse the ranking · Algorithm version 1.1 · Computed 2026-09-17

Call For Papers

ICAIM 2027 (International Conference on Artificial Intelligence & Materials) is an academic conference held in Changsha, China on 2027-03-12. The paper submission deadline is 2027-01-10. Acceptance notifications are sent on 2027-02-20.

The International Conference on Artificial Intelligence and Materials (ICAIM) committed to the deep integration and common enhancement in materials science, artificial intelligence (AI) technology. Topics of interest for submission include: Artificial Intelligence Adaptive Systems Fuzzy Logic Data Mining Machine Learning Deep Learning Inductive Learning Intelligent and Knowledge Based System Natural Language Processing Signal Processing Computer Vision Virtual Reality Augmented Reality Hybrid and Nonlinear system Intelligent Control Bioinformatics Pattern Recognition Knowledge Discovery Intelligent Data Analysis Neural Networks Genetic Algorithms Medical Diagnostics S upport Vector Machines Machine Vision Intelligent Systems and Language Materials Nanomedical materials Regenerative biomaterials Materials with engineered interfaces Self-assembled materials Materials with selective mechanical and functional properties Materials for soft and hard tissue reconstruction and regeneration 3D/4D printing for bioactive materials Hydrogen Energy Materials Biomass Energy Materials Geothermal Energy Materials Nuclear Materials Environmental Friendly Materials Electrolyte Materials Photovoltaic Materials Semiconductors and Semiconductor Devices Superconductors and Superconducting Materials Advanced manufacturing materials Catalyst Materials Light Emitting Materials Acoustic Materials Structured Materials AI & Materials Biomaterials modeling, design, and AI applications AI for materials science Digital twin technology with AI for materials industry Modelling techniques for manufacturing processes and systems boosted with AI Materials theory assisted by AI technology Novel AI lgorithms that have potential applications to materials AI in Materials Informatics and Data-Driven Research AI for Sustainable Materials Development AI for Predicting Material Failure and Durability AI-Enhanced Materials for Energy Applications AI in Advanced Manufacturing and Materials Processing Machine Learning for Computational Materials Science AI-Driven Materials Discovery and Design
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