Call for Participation
We encourage participation on topics that explore any form of synergy between scientific principles and AI/machine learning (ML) methods. Examples of relevant submissions include (but are not limited to):
AI/ML algorithms that employ soft or hard scientific constraints in the learning process.
Methods to encode scientific knowledge in AI/ML model architecture.
Science guided generative or reinforcement learning methods
Approaches that use scientific knowledge for post-facto verification of AI results along the lines of explainable AI.
AI models that employ science knowledge as ‘hints’ (i.e., weak supervision with scientific knowledge).
Surrogate and reduced order modeling methods.
Discovery of governing equations from data using AI models.
Hybrid constructions of science-based & AI/ML-based models.
Software development facilitating the inclusion of scientific knowledge in learning
Novel techniques in inverse modeling & system identification with AI.
Novel techniques for using data to calibrate parameters and system states in scientific models.
We are soliciting paper submissions for position, review, or research articles in two formats: (i) short papers (2-4 pages) and (ii) full papers (6-8 pages). Extended versions of articles in submission at other venues are acceptable as long as they do not violate the dual-submission policy of the other venue. We also encourage early drafts of on-going research with preliminary insights/results that contribute to the symposium agenda. All submissions will undergo peer review and authors will have the option to publish their work in an open access proceedings site.
Submissions should be formatted according to the AAAI template (see Author Kit) and submitted via EasyChair. All submissions will undergo double-blind peer review before acceptance.