The Doctoral Consortium offers PhD students a unique opportunity to present their ongoing research, receive expert feedback, and build connections with the research community.
The Doctoral Consortium is a dedicated session of WAILS 2026 designed specifically for PhD students working on topics related to AI and learning sciences. It provides a supportive and constructive environment where doctoral researchers can:
The Doctoral Consortium is open to PhD students at any stage of their doctoral research. We particularly encourage students who have a clear research direction but whose work is not yet finalized, the consortium is designed to help, not to evaluate completed theses.
Submissions should be written in English and formatted according to the Springer LNCS style. Doctoral Consortium papers are limited to a maximum of 6 pages (references, figures, tables, proofs, appendixes, acknowledgments, and any other content count toward the page limit). The paper should describe:
Unlike full and short papers, Doctoral Consortium submissions are not anonymized, the student's name and affiliation should appear on the paper.
Each submission will be reviewed by the Doctoral Consortium Chairs, with input from senior members of the Program Committee.
Please submit via CMT — select the WAILS 2026 Doctoral Consortium track at submission.
Each accepted doctoral student will be paired with a senior researcher mentor prior to the workshop. The mentor will provide written feedback on the submitted paper and engage in a dedicated one-on-one discussion during the consortium session.
The consortium session itself is structured as a series of short presentations (approximately 10–15 minutes each), followed by an open discussion with the audience and the assigned mentor. The goal is not to evaluate the work, but to help doctoral students refine their research questions, strengthen their methodology, and connect with the broader community.
Accepted Doctoral Consortium papers will be included in the workshop proceedings published by Springer LNCS.
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.