AI4Mat-NeurIPS-2026: NeurIPS-2026 Workshop on AI for Accelerated Materials Design
Abstract
AI4Mat-NeurIPS-2026 explores applications of AI to materials via: (1) AI-Guided Materials Design; (2) Automated Chemical Synthesis; and (3) Automated Material Characterization. As the focused meeting point for the AI-for-materials community at NeurIPS, the workshop emphasizes structured, expert-driven dialogue on making machine learning more impactful for real-world materials discovery. As reasoning models mature and self-driving laboratories come online, a timely question arises: how does compute translate into genuine scientific discovery, and how do we close the gap between algorithmic progress and deployment in messy, real experiments? Our two main sessions address this: Scaling Laws for Materials Reasoning: From Compute to Scientific Discovery examines reasoning models and the utility of compute; Automating Discovery That Delivers: When AI Meets the Messiness of Real Experiments tackles the critical challenges of real-world experimental data collection. Beyond invited talks, a substantial portion of the program is devoted to contributed spotlights, a poster session, and a town hall. Building on previous AI4Mat workshops, we strengthen this community through in-depth peer feedback on spotlight presentations, an expanded travel grant program, and a dedicated focus collection in a high-impact journal. Our location preference is Sydney to broaden the reach of the AI4Mat community.