Topics of Interest

We seek contributions in, but not limited to, the following areas:

Foundational Techniques in Machine Learning and AI

Learning from Diverse and Complex Data

Data-Centric AI and Data Engineering

Scalable and Real-Time Data Analytics

Interactive and Visual Analytics

Responsible, Causal, and Explainable AI

Applied Data Science and ML Across Domains

• Supervised, unsupervised, semi-supervised and self-supervised learning.
• Deep learning and representation learning.
• Reinforcement learning and federated learning.
• Transfer learning, meta learning, few-shot and continual learning.
• Multitask and multimodal learning.
• Generative models, including GANs and diffusion models.
• Large Language Models (LLMs) and Large Multimodal Models (LMMs).
• Zero-shot and prompt-based learning.
• Analytics over structured, semi-structured, and unstructured data.
• Text, time-series, graph, spatial, spatio-temporal, and network data.
• Web, social media, multimedia, IoT, and sensor data.
• Sequential, temporal, and dynamic data modelling.
• Data preprocessing, cleaning, integration, matching, and linkage.
• Privacy-preserving and secure data mining.
• Data-centric AI pipelines and dataset curation.
• Computational aspects of data mining and large-scale data management.
• Big data analytics and scalable ML.
• Parallel and distributed learning algorithms.
• Data stream mining and real-time analytics.
• Edge, cloud, and IoT-enabled ML systems.
• Visual analytics and explainability through visualisation.
• Human-in-the-loop machine learning.
• Interactive data exploration and decision support.
• Explainable and interpretable machine learning.
• Fairness, accountability, transparency, and ethics in AI.
• Causal inference and causal machine learning.
• Robustness, generalization, and uncertainty quantification.
• Applications in business, finance, education, agriculture, urban planning, healthcare, sports, social sciences, cybersecurity, arts, and humanities.
• Domain-specific AI systems in biomedical informatics, environmental science, astronomy, engineering, and more.
• Industrial case studies and data-driven product innovations.

Submission

We invite three types of submissions for AusDM'26. They are:

• Research Track: Submissions reporting on novel algorithms, models or theories; foundational or empirical research; and methodological advances. The paper length should be between 8 and 15 pages in Springer CCIS style, as detailed on conference website.
• Application Track: Submissions reporting on authentic and practical implementations and case studies; industry or government deployments; and lessons learned, impacts, and domain-specific innovations. The paper length should be between 6 and 15 pages in Springer CCIS style, as detailed on conference website.
• Late-Breaking Work Track: Submission presenting emerging ideas, innovative techniques, and early results that can benefit from timely discussion within the community. The paper length should be between 6 and 12 pages in Springer CCIS style, as detailed on conference website.

All submissions will go through a double-blind review process, i.e. paper submissions must NOT include authors names or affiliations or acknowledgments referring to funding bodies. Self-citing references should also be removed from the submitted papers for the double-blinded reviewing purpose. The information can be added in the accepted final camera-ready submissions.

Note that AusDM'26 upholds the principles of Diversity, Equity, and Inclusion (DEI). We encourage authors to:

1. avoid language or examples that reinforce marginalization or stereotypes;
2. be respectful and inclusive in how research is framed and presented.

If Generative AI tools (such as ChatGPT or others) are used in preparing the submission, authors must:

1. clearly disclose how these tools were used (e.g., for writing, data processing, visualisation, experimentation, etc.);
2. ensure the accuracy, originality, and correctness of all content generated;
3. maintain full responsibility for the integrity of the submission.

Publication

All accepted peer-reviewed papers will be published by Springer in the Communications in Computer and Information Science (CCIS) series and will be made available via SpringerLink. Previous AusDM proceedings can be accessed here.

At least one author per accepted paper must register and present at the conference for inclusion in the proceedings, and one registration covers only one paper.

A selected number of best papers will be invited for a submission to AusDM Special Issue in a Scimago ranked journal (TBC).

Important Dates (AoE, 11.59pm)

1. Research and Application Tracks:
   • Abstract submission: 5 July 26
   • Paper submission: 12 July 26
   • Paper Notification: 10 Aug 26
   • Camera-Ready Submission: 6 Sept 26
2. Late-Breaking Work Track:
   • Paper submission: 23 Aug 26
   • Paper Notification: 14 Sept 26
   • Camera-Ready Submission: 21 Sept 26