The Tutorial and Lab Forum is a regular and exciting event held at AAAI. It offers researchers to give a broad introduction to a field, a tool, or a method of inquiry that they may have been working on for several years. Ideally, a Tutorial would be accessible to a wide swath of the AAAI audience and bring them up to date on emerging or well-established tools and techniques. The Tutorial and Lab forum offers a longer, more in-depth experience than a research talk. For the last several years there have been two co-chairs for this position, with one chair carrying over from the previous year. This year Michael Katz (IBM) is serving in his first year and Nicholas Mattei (Tulane) is serving his second.
The Tutorial and Lab Forum Chairs are responsible for overseeing the full lifecycle of the tutorials and labs program, a major educational component of the conference. This role involves issuing the call for proposals, defining submission requirements and deadlines, and managing the review and selection process so that high-quality tutorials and labs are presented to attendees. The chairs work closely with the broader conference organizers to ensure that the selection of tutorial topics aligns with the overall scientific goals of the event and provides broad educational value across different AI subfields.
The tutorial chairs play a strategic and curatorial role in shaping the educational impact of AAAI’s tutorial program. Tutorials and labs are designed to offer deep dives into emerging and foundational topics in artificial intelligence, serving researchers, practitioners, and students alike. The chairs curate a balanced program that reflects both cutting-edge research and accessible introductions to complex areas outside many attendees’ core expertise. They ensure that the tutorials are structured and scheduled in ways that maximize participation and complement the main technical program, supporting the conference mission of facilitating knowledge exchange and continuing education across the AI community.
This year we received over 60 submissions that span the true breadth of work that AAAI publishes: from planning, to reasoning under uncertainty; and from formal methods to cutting edge machine learning and neural networks; with everything in between. Tutorials were selected primarily based on two factors: the quality and timeliness of the proposed presentation and the team as well as ensuring that the overall program had comprehensive coverage of the full breadth of AAAI topics. The full list of tutorials and labs is available here: https://aaai.org/conference/aaai/aaai-26/tutorial-and-lab-list/ and all these great presentations will happen on January 20 and 21 — We’re excited to see you there!