ΑΙhub.org
 

ACM SIGAI Industry Award 2022 nominations


by
10 May 2022



share this:

ACM SIGAI logo
The ACM SIGAI Industry Award for Excellence in Artificial Intelligence (AI) will be given annually to individuals or teams who have transferred original academic research into AI applications in recent years in ways that demonstrate the power of AI techniques via a combination of the following features: originality of the research novelty and technical excellence of the approach; importance of AI techniques to the approach; and actual or predicted societal impact of the application. Awardees receive a plaque accompanied by a prize of $5,000, and will be recognized at the International Joint Conference on Artificial Intelligence through an agreement with the IJCAI Board of Trustees.

After decades of progress in the theory, research and development of AI, AI applications are increasingly moving into the commercial sector. A great deal of pioneering application-level work is being done by those transferring research results into industry—from startups to large corporations—and this is influencing commerce and the broad public in a wide variety of ways. This award complements the numerous academic, best-paper and related awards, in that it focuses on innovators of fielded AI applications. It is intended especially to recognize those who are not only active in the academic community, but also playing key roles in AI commercialization. The award honors these innovators and highlights their achievements (and thus the benefit of AI techniques) to computing professionals and the public at large. The award committee will consider applications that are open-source or proprietary and that may or may not involve hardware.

Evaluation Criteria: The criteria include the following, but there is no fixed weighting of them:

  • Novelty of application area
  • Novelty and technical excellence of the approach
  • Importance of AI techniques for the approach
  • Actual and predicted societal benefits of the fielded application

Eligibility Criteria: Any individual or team, worldwide, is eligible for the award.

Nomination Procedure

One nomination and three endorsements must be submitted. The nomination must identify the individual or team members, describe their fielded AI system, and explain how it addresses the award criteria. The nomination must be written by a member of ACM SIGAI. Two of the endorsements must be from members of ACM or ACM SIGAI. Endorsements are intended to be brief statements of support (typically 1-2 paragraphs and should not exceed 1000 words) that provide additional perspective on the nomination itself.

If you are not a member of ACM SIGAI, please join here.

Please submit the nomination and endorsements through our Google form.

For any questions please contact Craig Boutilier (Award Chair) or Nicholas Mattei (SIGAI Vice Chair).

Timeline

Nominations Due: May 31, 2022
Award Announcement: June 30, 2022
Award Presentation: July 23 – 29 at IJCAI 2022.




ACM SIGAI Association for Computing Machinery Special Interest Group in Artificial Intelligence
ACM SIGAI Association for Computing Machinery Special Interest Group in Artificial Intelligence




            AIhub is supported by:



Related posts :



Forthcoming machine learning and AI seminars: December 2025 edition

  01 Dec 2025
A list of free-to-attend AI-related seminars that are scheduled to take place between 1 December 2025 and 31 January 2026.
monthly digest

AIhub monthly digest: November 2025 – learning robust controllers, trust in multi-agent systems, and a new fairness evaluation dataset

  28 Nov 2025
Welcome to our monthly digest, where you can catch up with AI research, events and news from the month past.

EU proposal to delay parts of its AI Act signal a policy shift that prioritises big tech over fairness

  27 Nov 2025
The EC has proposed delaying parts of the act until 2027 following intense pressure from tech companies and the Trump administration.

Better images of AI on book covers

  25 Nov 2025
We share insights from Chrissi Nerantzi on the decisions behind the cover of the open-sourced book ‘Learning with AI’, and reflect on the significance of book covers.

What is AI poisoning? A computer scientist explains

  24 Nov 2025
Poisoning is a growing problem in the world of AI – in particular, for large language models.

New AI technique sounding out audio deepfakes

  21 Nov 2025
Researchers discover a smarter way to detect audio deepfakes that is more accurate and adaptable to keep pace with evolving threats.

Learning robust controllers that work across many partially observable environments

  20 Nov 2025
Exploring designing controllers that perform reliably even when the environment may not be precisely known.



 

AIhub is supported by:






 












©2025.05 - Association for the Understanding of Artificial Intelligence