AI4Mat-NeurIPS 2026

Deadlines
Machine Learning/CORE Unranked

AI4Mat-NeurIPS 2026

AI for Accelerated Materials Design - NeurIPS 2026

Dec 11 2026Sydney, AustraliaOfficial conference site Site reachable

AI4Mat-NeurIPS 2026 is a workshop focused on the intersection of artificial intelligence and materials science, aiming to foster collaboration between researchers in machine learning and materials discovery. It provides a platform for presenting novel AI-driven methods for materials design, characterization, and property prediction, aligned with the NeurIPS conference.

Key deadlines

Verified September 9, 2026

Full paper

August 30, 2026

AoE

Conference timeline

Submission and decisions

Full paperKey deadline

August 30, 2026 · AoE

Paper fit

Contribution paths

A strong submission should clearly identify its contribution and evaluate it appropriately.

Full Papers

Original research contributions with substantial technical depth and experimental validation.

Short Papers

Preliminary results, novel ideas, or work-in-progress with clear potential for impact.

Datasets and Benchmarks

Publicly available datasets, curated benchmarks, or evaluation protocols for AI in materials science.

Software Tools

Open-source software, libraries, or frameworks that enable AI research in materials science.

Research areas in scope

01

Research Topics

Machine learning for materials discoveryGenerative models for materials designPhysics-informed neural networks for materialsMultimodal learning for materials dataExplainable AI for materials scienceActive learning and Bayesian optimization for materials experimentsGraph neural networks for molecular and crystal structuresTransfer learning across materials datasetsAI for high-throughput screening and property predictionAI-driven characterization of materials (e.g., microscopy, spectroscopy)Data curation and benchmark datasets for materials AIAI for sustainable materials and green chemistryAI for quantum materials and topological systemsIntegration of AI with computational materials physics (DFT, MD)

Policies worth checking twice

  • Submissions must be anonymized for double-blind review.
  • Full papers are limited to 8 pages, short papers to 4 pages, excluding references.
  • Dual submission to other peer-reviewed venues is not allowed during review.
  • Author lists and affiliations may not be changed after the submission deadline.
  • All submissions must include a statement on the use of AI tools in the research and writing process.

Official sources

Compiled from the official call for papers. The organizers’ pages remain authoritative.

Last verified September 9, 2026