Full Papers
Submissions must follow the NeurIPS 2026 template and are limited to 9 pages for main content, with unlimited pages for references and appendices. Accepted papers may add 1 additional page (10 pages total) for the camera-ready version.
AI/CORE Unranked
CAPMW 2026
The First Conference on AI for Physics at MeaWorm Corp 2026
CAPMW 2026 is the inaugural conference dedicated to AI for physics, bringing together researchers from physics, computer science, and AI to explore how modern AI methods are transforming scientific discovery, simulation, and understanding of physical systems. Hosted by MeaWorm Corp in Hangzhou, the hybrid event features keynote talks, peer-reviewed paper presentations, and networking opportunities to foster interdisciplinary collaboration.
Paper fit
Contribution paths
A strong submission should clearly identify its contribution and evaluate it appropriately.
Research areas in scope
01
AI for Scientific Discovery
Machine learning approaches for discovering new physical laws, equations, and relationships from experimental or simulated data.
02
AI for Particle & High-Energy Physics
Applications in collider physics, neutrino detection, dark matter searches, and event reconstruction.
03
AI for Astrophysics & Cosmology
Surveys, gravitational wave analysis, exoplanet detection, large-scale structure modeling, and cosmological parameter estimation.
04
AI for Quantum Physics
Quantum state tomography, quantum control, variational quantum algorithms, and quantum error correction.
05
AI for Condensed Matter & Materials
Property prediction, materials discovery, phase transition identification, and many-body system modeling.
06
AI for Fluid Dynamics & Plasma Physics
Turbulence modeling, surrogate simulations, plasma control, and reduced-order modeling.
07
AI for Biophysics & Complex Systems
Protein folding, molecular dynamics acceleration, biological network analysis, and emergent behavior prediction.
08
Physics-Informed Machine Learning
Physics-informed neural networks (PINNs), neural operators, symbolic regression, and equation learning.
Policies worth checking twice
- Submissions must be double-blind; author names and affiliations must be omitted.
- Submissions concurrently under review at other venues are acceptable.
- All accepted papers will be non-archival and publicly available.
- At least one author must register for the conference to present the work.
- Both in-person and virtual presentation options will be available.
- Submissions must follow the NeurIPS 2026 template (LaTeX or Word).
Official sources
Compiled from the official call for papers. The organizers’ pages remain authoritative.
Last verified September 9, 2026