The topics of interest for submission include, but are not limited to:
◕ Track 1: Materials Informatics and Data-Driven Discovery
Materials databases, data curation, and standardization
Feature engineering and representation learning for materials
Machine learning workflows for materials discovery
Multi-modal data fusion (experimental, computational, and literature data)
Data-efficient learning with limited, sparse, or noisy materials data
Uncertainty quantification and reliability assessment of data-driven models
Visualization and interpretability of materials data and predictions
...
◕ Track 2: Predictive Modeling and AI-Driven Materials Design
Structure–property and composition–property prediction using AI
Graph neural networks and deep learning for materials modeling
Inverse design frameworks for targeted material properties
Generative models for novel material candidates
Surrogate modeling for accelerating simulations and optimization
Hybrid physics-based and data-driven modeling approaches
Multi-scale and multi-physics materials prediction
...
◕ Track 3: Autonomous Experimentation and Intelligent Workflows
AI-enabled high-throughput computational screening
Autonomous and self-driving laboratories for materials research
Active learning and Bayesian optimization in materials experiments
Closed-loop integration of AI, synthesis, and characterization
Robotic platforms for automated materials fabrication and testing
Digital twins and real-time decision-making systems
Intelligent control of experimental and processing workflows
...
◕ Track 4: AI-Enabled Functional and Advanced Materials Applications
AI-guided design of energy and environmental materials
Intelligent optimization of materials synthesis and manufacturing processes
AI applications in polymers, composites, and multifunctional materials
Materials for electronics, photonics, and next-generation devices
Sustainable and eco-friendly materials development using AI
AI for materials performance optimization and lifecycle analysis
Translation of AI-driven materials research to real-world applications
...