FoIKS 2024
13th International Symposium on Foundations of Information and Knowledge Systems
April 8 - 11 • Sheffield, UK


Important Dates

All deadlines are at 23:59 UTC-12 (AoE, "anywhere on earth").
  1. Abstract submission deadline (long and short papers): 11.12.2023 (extended)
  2. Paper submission deadline (long and short papers): 14.12.2023 (extended)
  3. Acceptance notifications: 29.01.2024
  4. Camera-ready versions of accepted papers due: 08.02.2024
  5. Early registration deadline: 11.03.2024
  6. Late registration deadline: 21.03.2024
  7. Conference: 8-11.04.2024

SCAM WARNING: Some attendees have received scam emails regarding their accommodation during FoIKS. We will contact you only via easychair, university email, or website. Furthermore, we will *not* contact you regarding bookings of accommodation or travel.

About FoIKS

The FoIKS symposia provide a biennial forum for presenting and discussing theoretical and applied research on information and knowledge systems. The goal is to bring together researchers with an interest in this subject, share research experiences, promote collaboration and identify new issues and directions for future research.

FoIKS 2024 solicits original contributions (as well as extensions of previously published contributions) dealing with any foundational aspect of information and knowledge systems. This includes submissions that apply ideas, theories or methods from specific disciplines to information and knowledge systems. Examples of such disciplines are discrete mathematics, logic and algebra, model theory, information theory, (parameterized) complexity theory, algorithmics and computation, statistics, and optimisation, among, of course, many others.

The FoIKS symposia are a forum for intensive discussions. Speakers will be given sufficient time to present their ideas and results within the larger context of their research. Furthermore, participants will be asked to prepare a first response to another contribution in order to initiate discussion.


Centre for Machine Intelligence