The Senior Member Presentation Track (SMPT) provides an opportunity for established researchers in the AI community to give a broad talk that (i) describes a vision for bridging AI communities; (ii) summarizes a well-developed research area; or (iii) presents promising ideas and visions for new research directions. These presentations should provide a big-picture view, in contrast to regular papers, which may focus on a specific contribution. Submissions include a proposal for a talk and a paper (in the AAAI format) covering the topic of the talk. Senior members of AI are researchers who are well-established in their research area.

Senior Member Track Schedule

Tracks with Accepted Papers

Bridge Talks

New AI communities often emerge when two or more disciplines come together in order to explore new opportunities and perspectives; today both are plentiful. The purpose of a Bridge Talk is to describe an opportunity for cultivating sustained collaboration between two or more communities, directed towards a common goal.

The Fairness Fair: Bringing Human Perception into Collective Decision-Making
Hadi Hosseini

Summary Talks

Broad talks on a well-developed body of research or an important new research area. These are expected to include results obtained by researchers other than the speaker and should include a well-thought-out critical analysis of the state-of-the-art, with suggestions for future directions.

Temporal Fairness in Multiwinner Voting
Edith Elkind; Svetlana Obraztsova; Nicholas Teh

Mixed Fair Division: A Survey
Shengxin Liu; Xinhang Lu; Mashbat Suzuki; Toby Walsh

Adventures of Trustworthy Vision-Language Models: A Survey
Mayank Vatsa; Anubhooti Jain; Richa Singh

Blue Sky Ideas Talks

These presentations aim to present ideas and visions that will stimulate the research community to pursue new directions; for example, new problems, new application domains, or new methodologies that are likely to stimulate significant new research. The presenter should find the right arguments to convince the audience that the topic is promising and should relate the talk as much as possible to the existing literature.

Model Reprogramming: Resource-Efficient Cross-Domain Machine Learning
Pin-Yu Chen

Regeneration Learning: A Learning Paradigm for Data Generation
Xu Tan; Tao Qin; Jiang Bian; Tie-Yan Liu; Yoshua Bengio

Towards a More Burkean Approach to Computational Social Choice
Omer Lev

Recommender Ecosystems: A Mechanism Design Perspective on Holistic Modeling and Optimization
Craig Boutilier; Martin Mladenov; Guy Tennenholtz

Conversational Modeling for Constraint Satisfaction
Eugene C. Freuder

Integrated Systems for Computational Scientific Discovery
Pat Langley

For More Information

Inquiries concerning submissions and suggestions for the senior member track may be directed to the track cochairs at aaai24smchairs@aaai.org. All other inquiries should be directed to AAAI at aaai24@aaai.org.

Senior Member Track Cochairs

Kate Larson (University of Waterloo, Canada)

David Poole (University of British Columbia, Canada)

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