AusDM: Australasian Data Mining Conference

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Past:   Proceedings on DBLP

Future:  Post a CFP for 2025 or later   |   Invite the Organizers Email

 
 

All CFPs on WikiCFP

Event When Where Deadline
AusDM 2024 Australasian Data Mining Conference
Nov 25, 2024 - Nov 27, 2024 Melbourne, Australia Aug 11, 2024 (Aug 4, 2024)
AUSDM 2023 The Australasian Data Science and Machine Learning Conference 2023 - First Call for Papers
Dec 11, 2023 - Dec 13, 2023 Auckland, New Zealand Aug 25, 2023 (Aug 18, 2023)
AUSDM 2022 THE 20TH AUSTRALASIAN DATA MINING CONFERENCE 2022
Dec 12, 2022 - Dec 16, 2022 Western Sydney Aug 12, 2022 (Aug 5, 2022)
AusDM 2021 The 19th Australasian Data Mining Conference 2021
Dec 13, 2021 - Dec 15, 2021 Brisbane, Australia Sep 7, 2021
AusDM 2020 The 18th Australasian Data Mining Conference 2020
Dec 1, 2020 - Dec 4, 2020 Canberra, Australia Aug 7, 2020
AusDM 2019 The 17th Australasian Data Mining Conference
Dec 2, 2019 - Dec 5, 2019 Adelaide, Australia Aug 12, 2019
AusDM 2018 Australasian Data Mining Conference
Nov 28, 2018 - Nov 30, 2018 Bathurst, Australia Jul 20, 2018
AusDM 2017 15th Australasian Data Mining Conference
Aug 19, 2017 - Aug 25, 2017 Melbourne, Australia May 31, 2017
AusDM 2013 The 11th Australasian Data Mining Conference
Nov 13, 2013 - Nov 15, 2013 Canberra, Australia Jul 15, 2013
AusDM 2012 The 10th Australasian Data Mining Conference
Dec 5, 2012 - Dec 7, 2012 Sydney, Australia Aug 1, 2012
AusDM 2011 Ninth Australasian Data Mining Conference
Dec 1, 2011 - Dec 2, 2011 Ballarat, Victoria, Australia Aug 22, 2011 (Jun 24, 2011)
AusDM 2009 The Australasian Data Mining Conference
Dec 1, 2009 - Dec 4, 2009 Melbourne, Australia Jul 31, 2009
AusDM 2008 The Australasian Data Mining Conference
Nov 27, 2008 - Nov 28, 2008 Adelaide, Australia Aug 1, 2008
 
 

Present CFP : 2024

Australasian Data Science and Machine Learning Conference - 25th to 27th November 2024
Melbourne, Australia

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Call for Papers
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The Australasian Data Science and Machine Learning Conference (AusDM), formerly known as the Australasian Data Mining Conference, has established itself as the premier Australasian meeting for both practitioners and researchers in the fields of Data Science including but not limited to Data Analytics and Data Mining theory and applications and Machine Learning including but not limited Deep Learning and Generative AI. Despite the evolution of these interdisciplinary fields, AusDM is devoted to the art and science of intelligent learning and analysis of (usually big) data sets for meaningful (and previously unknown) insights that could be actionable. Hence, it enables the sharing and learning of research and progress in the local context and breakthroughs in these interdisciplinary fields.

Since AusDM’02, the conference has been providing a forum for disseminating, presenting, showcasing and discussing the latest research and developments in all aspects of Data Science and Machine Learning, including algorithms, software, systems and applications across all industries. Built on this tradition, AusDM’24 will facilitate the cross-disciplinary exchange of ideas, experiences, practices and potential research directions. Specifically, the conference seeks to showcase: Research Prototypes, Industry Case Studies, Practical Technology, and Research Student Projects.

It is aimed to be a meeting place for pushing forward the frontiers of Data Science and Machine Learning in academia and industry. Thus, AusDM’24 will have a variety of engaging activities such as keynote speeches, panel discussions, full paper presentations, tutorials/ workshops, doctoral consortium, social/ networking events, etc.


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Key Dates (Timezone: AoE)
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Abstract submission: 4 Aug 24
Paper submission: 11 Aug 24
Paper notification: 8 Sept 24
Camera-ready: 22 Sept 24
Author Registration: 22 Sept 24
Conference dates: 25 to 27 Nov 24


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Topics of Interest
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We are calling for papers, both research and applications, and from both academia and industry, for publication and presentation at the conference. All papers will go through double-blind peer review by a panel of international experts.

Please note that AusDM’24 requires that at least one author for each accepted paper register for the conference and present their work for the paper to be published in the proceeding.

AusDM’24 invites contributions addressing current research in Data Science and Machine Learning as well as the experiences, practices, novel applications and future challenges. Topics of interest include, but are not restricted to:

-Data analytics and machine learning over heterogenous data sources including structured, semi-structured, unstructured such as text, graph, sequential, temporal, spatial, spatial-temporal, network, real-time, streaming, web, social media, multimedia, IoT, etc.
-Big data mining and analytics, parallel and distributed data mining and analytics, data stream mining and analytics
-Computational aspects of data mining and data management
-Privacy-preserving data mining and analytics
-Data pre-processing, integration, matching, and linkage
-Visual analytics and interactive data exploration
-Machine learning, deep learning, representation learning, reinforcement learning, federated learning
-Few-shot learning, transfer learning, meta learning, continual learning, multitask learning, multimodal learning
-Zero-short learning, generative modelling, Large Language Models (LLMs), Large Multimodal Models (LMMs)
-Causal and explainable machine learning
-Ethical and responsible AI
-Applications of data science and machine learning in various disciplines such as business, social sciences, education, urban planning, engineering, biomedical and health, sports, humanities, arts, cybersecurity, security and surveillance, environmental science, astronomy, etc.


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Submissions
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AusDM’24 proceedings will be published by Springer Communications in Computer and Information Science (CCIS) and made available in due course. The previous AusDM proceedings on SpringerLink is available here (https://link.springer.com/conference/ausdm).

We invite three types of submissions for AusDM’24:

-Research Track: Academic submissions reporting on new algorithms, novel approaches and research progress, with a paper length of between 8 and 15 pages in Springer CCIS style, as detailed on conference website.

-Application Track: Submissions reporting on authentic and practical applications, implementations and experiences or practices. Submissions in this category can be between 6 and 15 pages in Springer CCIS style, as detailed on conference website.

-Industry Showcase Track: Submissions from governments and industry sectors on solutions that have raised profits, reduced costs and/or transformed policy and/or business outcomes/ models can be made in this track. Submissions to this category should be a 1-page extended abstract. Please note that this track is presentation only, without publication in conference proceedings. For publication of your papers, please submit them to the above Application Track.

All submissions, except for the Industry Showcase Track, will go through a double-blind review process, i.e. paper submissions must NOT include authors names or affiliations or acknowledgements 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.

AusDM24 values and promotes Diversity, Equity and Inclusion (DEI) in the community and profession. We would like to remind authors to be mindful of not using language or examples that further the marginalisation, stereotyping, or removing of any groups of individuals, especially the marginalised and/or under-represented groups in computing during paper writing.

If Generative AI including Large Language Models (LLMs) is used to assist in preparing the paper submissions, authors are expected to fully describe how Generative AI is used and ensure that all content (e.g. text and figures) of the paper are correct and original. For example, authors should provide how the Generative AI tools were used for paper writing, data processing/ filtering, visualisation, facilitating or running of experiments and proving theorems.


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Journal Special Issue
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A selected number of best papers will be invited for a submission to AusDM Special Issue in a Scimago ranked journal. The information of past Special Issue is available below:
AusDM22 Special Issue (https://link.springer.com/article/10.1007/s41019-024-00247-w)
AusDM23 Special Issue (https://link.springer.com/collections/feciibbfdd)
 

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