Call for Participation

We encourage participation on topics that explore any form of synergy between scientific principles and AI/machine learning/data mining/high-performance computing methods. Examples of relevant topics include (but are not limited to):

  1. Use of physical constraints or priors in supervised and unsupervised AI methods,

  2. Approaches to encode scientific knowledge in deep learning architectures,

  3. Physics-guided generative and reinforcement learning methods,

  4. Discovery of physically interpretable laws from data,

  5. Hybrid constructions of physics-based and machine learning models,

  6. Architectural and algorithmic improvements enabled by AI in scientific computing,

  7. Software development facilitating the inclusion of physics in AI, and

  8. Use of AI 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 (https://easychair.org/my/conference?conf=fss20). All submissions will undergo double-blind peer review before acceptance.