The 38th Annual AAAI Conference on Artificial Intelligence
February 20-27, 2024 | Vancouver, Canada
Senior Member Presentation Track
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.
Tracks with Accepted Papers
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
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
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
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
For More Information
Inquiries concerning submissions and suggestions for the senior member track may be directed to the track cochairs at email@example.com. All other inquiries should be directed to AAAI at firstname.lastname@example.org.
Senior Member Track Cochairs
Kate Larson (University of Waterloo, Canada)
David Poole (University of British Columbia, Canada)