Inaugural Edition

CAPMW 2026

The First Conference on AI for Physics at MeaWorm Corp

๐Ÿ“… November 15โ€“17, 2026 ๐Ÿ“ MeasuringWorm Corp, Hangzhou, Zhejiang ๐ŸŒ Hybrid (In-person & Virtual)

About the Conference

CAPMW 2026 brings together researchers at the intersection of artificial intelligence and physics to explore how modern AI methods are transforming scientific discovery, simulation, and understanding of physical systems.

Hosted at MeaWorm Corp, this inaugural conference aims to foster interdisciplinary collaboration between physicists, computer scientists, and AI researchers. We seek to identify emerging challenges in applying AI to physics problems, discuss novel methodological solutions, and explore new perspectives across the full theoryโ€“algorithmโ€“application stack.

The conference will feature keynote talks from leading experts, peer-reviewed paper presentations, poster sessions, and dedicated networking events designed to spark new collaborations.

Call for Papers

We invite submissions on all topics related to AI for physics, including but not limited to:

๐Ÿ”ฌ

AI for Scientific Discovery

Machine learning approaches for discovering new physical laws, equations, and relationships from experimental or simulated data.

โš›๏ธ

AI for Particle & High-Energy Physics

Applications in collider physics, neutrino detection, dark matter searches, and event reconstruction.

๐ŸŒŒ

AI for Astrophysics & Cosmology

Surveys, gravitational wave analysis, exoplanet detection, large-scale structure modeling, and cosmological parameter estimation.

๐Ÿ”ฎ

AI for Quantum Physics

Quantum state tomography, quantum control, variational quantum algorithms, and quantum error correction.

๐Ÿงช

AI for Condensed Matter & Materials

Property prediction, materials discovery, phase transition identification, and many-body system modeling.

๐ŸŒŠ

AI for Fluid Dynamics & Plasma Physics

Turbulence modeling, surrogate simulations, plasma control, and reduced-order modeling.

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AI for Biophysics & Complex Systems

Protein folding, molecular dynamics acceleration, biological network analysis, and emergent behavior prediction.

๐Ÿ–ฅ๏ธ

Physics-Informed Machine Learning

Physics-informed neural networks (PINNs), neural operators, symbolic regression, and equation learning.

Important Dates

June 6, 2026

Paper Submission Opens

September 6, 2026

Paper Submission Deadline

All submissions due by 23:59 AoE (Anywhere on Earth)

September 30, 2026

Review Decisions Announced

October 15, 2026

Camera-Ready Deadline

November 15โ€“17, 2026

Conference Dates

Submission Guidelines

๐Ÿ“„ Format

Submissions must follow the NeurIPS 2026 template (LaTeX or Word). Papers 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.

๐Ÿ”’ Anonymity

The review process is double-blind. Please anonymize your submissions and remove any links or information that may reveal author identity. Author names and affiliations should be omitted from the submitted PDF.

๐ŸŒ Submission Portal

All papers must be submitted through the OpenReview platform:

Submit via OpenReview โ†’

๐Ÿ“‹ Policies

  • 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.

Organizing Committee

๐Ÿ‘ค

Chengtian Liang

General Chair

MeaWorm Corp

๐Ÿ‘ค

Fan Yang

Program Chair

MeaWorm Corp

Interested in reviewing? Contact us to join the reviewer pool.

Contact

For questions about submissions, registration, or the conference program, please reach out to: