Proposed Special Session Topics

MAID 2027 will set up the following special sessions. Please select the session you are willing to organize and provide necessary information as required.

• TRACK 1 Machine Learning Potentials & Force Fields ML-based interatomic potentials for accelerated materials simulations, including neural network potentials, Gaussian approximation potentials, and equivariant models.
• TRACK 2 Generative Models for Materials Design GANs, diffusion models, VAEs, and transformer-based architectures for inverse design, crystal structure prediction, and de novo molecule generation.
• TRACK 3 High-Throughput Computational Screening DFT-based and ML-accelerated virtual screening of large chemical spaces, materials databases, and automated workflow pipelines.
• TRACK 4 Autonomous Laboratories & Robotics Self-driving labs, automated synthesis platforms, robotic experimentation, and closed-loop AI-driven optimization of materials properties.
• TRACK 5 Multimodal Data Fusion & LLMs Integrating text, images, spectral data, and simulation results with large language models, vision-language models, and multimodal foundation models for materials science.
• TRACK 6 Physics-Informed ML & Uncertainty Quantification Embedding physical constraints, symmetries, and conservation laws into ML models; Bayesian methods and conformal prediction for reliable materials property prediction.
• TRACK 7 AI for Sustainable & Energy Materials Applications to batteries, catalysts, photovoltaics, thermoelectrics, CO₂ capture, and hydrogen storage materials.