Adaptive Learning and Intelligent Systems, 2027

Call for papers:

We are pleased to announce the Artificial Intelligence track on Adaptive Learning & Intelligent Systems, as part of the Australasian Computer Science Week (ACSW) to be held in Canberra in 2027 (exact dates TBA). ALIS aims to bring together researchers, practitioners, and industry leaders across all fields of Artificial Intelligence with a focus on modern, cutting-edge AI methods, including deep learning, reinforcement learning, generative AI, and large language models as well as their theoretical foundations and real-world applications 

Venue:

Canberra (further details TBA) 

Scope and Topics:

We invite high-quality submissions on all areas of AI, with particular emphasis on learning-based and adaptive systems. Topics of interest include, but are not limited to:

• Generative AI: foundation models, multimodal generative systems, controllability, evaluation, safety

• Agentic AI systems: autonomous agents, planning, agent collaboration, evaluation and safety

• Deep Learning Advances: architectures, training methods, interpretability, scalability

• Graph Neural Networks- based architectures, representations and applications

• Reinforcement Learning & Control: single-agent, multi-agent, hierarchical RL, safe and explainable RL

• Large Language Models (LLMs): reasoning, alignment, fine-tuning, efficient deployment, societal impact

• Quantum Machine Learning, variational quantum algorithms, quantum-enhanced optimization, hybrid quantum–classical models

• Adaptive Systems: online learning, continual learning, meta-learning, self-improving AI

• Cognitive & Neurosymbolic AI: hybrid approaches, reasoning and learning integration

• Trustworthy AI: fairness, robustness, explainability, human-centered design, responsible deployment

• Applications: healthcare, robotics, education, finance, climate, creative industries

• Multimodal Learning: vision-language models, multimodal representation learning, image/video understanding, cross-modal learning

• Embodied AI & Robot Learning: perception, manipulation and navigation, vision-language-action models, human–robot interaction

• Privacy and Security: privacy-preserving learning, federated learning, adversarial learning, AI security

Submission Guidelines:

Please submit your papers via easychair at: https://easychair.org/conferences/?conf=acsw2027 

Full Papers: Paper length of up to 8 pages, excluding references and appendices. 

Short Papers: Paper length of 2-4 pages, excluding references and appendices. 

Submissions must be original and unpublished.  Papers submitted to arxiv or other non-archival venues can be submitted to ALIS.

All papers will undergo double-blind peer review.

Recommended template: double column format in Latex or Word. 

All submissions will undergo double-blind peer review. So please make sure author details and other identifying information is removed from the initial submissions.

Important Dates:

Abstract submission deadline: 20th November, 2026

Main paper submission deadline: 27th November, 2026

Decision Notification: 10th January, 2027 (tentative)

Conference Dates: TBA (Between 1st to 5th February, 2027)

Registration and Publication:

All accepted papers will be eligible to be published in the ACM Digital Library as part of the ACSW 2027 Proceedings.

Registration details will be available on the ACSW website: https://acsw.core.edu.au/