Award nominations open

Joint AAAI/ACM SIGAI Doctoral Dissertation Award

AAAI and ACM SIGAI are pleased to announce the continuation of the Joint AAAI/ACM SIGAI Doctoral Dissertation Award to recognize and encourage superior research and writing by doctoral candidates in artificial intelligence. The award is presented annually at the AAAI Conference on Artificial Intelligence, and the winner will be invited to present a talk at the conference.

A nominated dissertation must have been successfully defended (but not necessarily finalized) between October 1 of the previous year through September 30 of the current year. Nominations are welcome from any country, but only English language versions will be accepted. Only one nomination may be submitted per Ph.D. granting institution, including large universities. The nominator must be an ACM SIGAI member and/or AAAI member.

Nomination process:

Nominations are due by November 15, 2021. Nominations must be made by the thesis advisor; a complete nomination includes the following:

1. The names, affiliations, and contact information of the nominator and the candidate.
2. A nomination statement (200-300 words in length) that explains why the candidate should receive this award and addresses the significance of the dissertation. This should not simply repeat the information in the abstract.
3. A letter of endorsement from the department head (or dean), which also certifies that this is the only nomination being made from that institution.
4. Supporting letters (not less than two, and not more than three) from from experts in the field who can speak to the impact of the dissertation.
5. An electronic copy of the submitted dissertation.

Nominations must be sent in an email (with all the materials attached as a single file) to the chair of the award committee, Prof. Bart Selman (selman@cs.cornell.edu) by November 15, 2021, 11:59 PM anywhere in the world.

ACM SIGAI and AAAI are pleased to announce the winner of the 2019 AAAI/ACM SIGAI Dissertation Award, Jiajun Wu of the Massachusetts Institute of Technology, for his work entitled Learning to See the Physical World.

Two runners-Up were also honored: Aishwarya Agrawal of the Georgia Institute of Technology for Visual Question Answering and Beyond, and Li Dong of the University of Edinburgh for Learning Natural Language Interfaces with Neural Models. All winners will be honored during AAAI-21.