Conference Information

AJCAI 2026: Australasian Joint Conference on Artificial Intelligence

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Submission Date:
2026-07-15 Due in 14 days
Notification Date:
2026-08-25
Conference Date:
2026-11-26
Location:
Auckland, New Zealand
Years:
39
ICORE: B   QUALIS: B1   Viewed: 22083   Tracked: 6   Attend: 0

Call For Papers

AJCAI 2026 (Australasian Joint Conference on Artificial Intelligence) is a ICORE B / QUALIS B1 conference held in Auckland, New Zealand on 2026-11-26. The paper submission deadline is 2026-07-15. Acceptance notifications are sent on 2026-08-25.

Since the first AI Conference took place in Sydney in 1987, the series of the annual Australasian Joint Conference on Artificial Intelligence has become the premier event for Artificial Intelligence researchers in Australia and one of the major international forums on AI worldwide. As the largest city in New Zealand, Auckland is home to some of the country's most prominent research institutions, including the University of Auckland, Auckland University of Technology (AUT), and Massey University. This vibrant city serves as a hub of innovation and technology, making it an ideal setting for AI research that drives societal impact and informs decision-making. Auckland also hosts a thriving R&D ecosystem, bringing together leading businesses, government agencies, universities, and industry players in a united effort to address both regional and global AI challenges. Prospective authors are invited to submit original research and application papers in any area of Artificial Intelligence. Novel theories, algorithms, and applications about Foundation Models, Artificial Intelligence-Generated Content (AIGC), 3D Vision, Quantum Machine Learning, and explainable AI are highly welcome. The conference topics are, but not limited to, the following: Agent-based and multi-agent systems AI applications and innovations Cognitive modelling and computer-human interaction Commonsense reasoning Computer vision Constraint satisfaction, search, and optimisation Deep Learning Generative Models Evolutionary computation Explainable AI Fairness, Accountability and Transparency Fuzzy Systems Game playing and interactive entertainment Human-Robot Interaction Information retrieval, integration, and extraction Learning and Reasoning Integration Knowledge acquisition and ontologies Knowledge representation and reasoning Machine learning and data mining Model-based systems Multidisciplinary AI Natural language processing Neural Networks Planning and scheduling Robotics Social Robotics Social choice Uncertainty in AI Web and Information Systems Trustworthy Large Models
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Related Journals

CCFFull NameImpact FactorPublisherISSN
Australasian Journal of Engineering EducationTaylor & Francis1325-4340
AIEEE Transactions on Multimedia9.7IEEE1520-9210
CKnowledge-Based Systems7.2Elsevier0950-7051
BSoftware & Systems Modeling3.2Springer1619-1366
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CFuture Generation Computer Systems6.1Elsevier0167-739X
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