Call for Papers

We solicit papers in the context of scientific discovery and engineering design on topics including but not limited to:

  • Methods to combine scientific knowledge and data to build accurate predictive models
  • Adaptive experiment design under resource constraints
  • Learning cheap surrogate models to accelerate simulations
  • Learning effective representations for structured data
  • Uncertainty quantification and reasoning tools for decision-making
  • Explainable AI for both prediction and decision-making
  • Integrating AI tools into existing workflows
  • Domain specific languages and software tools for improved productivity
  • Challenges in applying and deployment of AI in the real-world

We welcome submissions of long (max. 8 pages), short (max. 4 pages), and position (max. 4 pages) papers describing research at the intersection of AI and science/engineering domains including chemistry, physics, power systems, materials, catalysis, health sciences, computing systems design and optimization, epidemiology, agriculture, forestry, transportation, earth and environmental sciences, genomics and bioinformatics, civil and mechanical engineering etc.

Submissions must be formatted in the AAAI submission format. All submissions should be done electronically via CMT.

Submission Site: https://cmt3.research.microsoft.com/AItoASE2026

The submission deadline is October 22nd, 2025 (11:59 PM PST).

The accepted papers will be considered non-archival.

CMT acknowledgement: The Microsoft CMT service was used for managing the peer-reviewing process for this conference. This service was provided for free by Microsoft and they bore all expenses, including costs for Azure cloud services as well as for software development and support.

Contact email: For questions, please email the lead organizer Aryan Deshwal or Jana Doppa.