Call for Papers

We invite submissions for our upcoming Special Session on Data Science: Foundations and Applications at The 21st International Conference Advanced Data Mining and Applications 2025 (ADMA 2025).

Background

Data science has evolved into a powerful interdisciplinary field, combining principles from statistics, computer science, and domain expertise to extract actionable insights from data. Its applications span a wide range of industries, including healthcare, finance, manufacturing, and social sciences. Despite significant advances, many challenges remain in ensuring that data-driven solutions are not only effective but also ethical, explainable, and generalizable across diverse contexts. This special session aims to explore both foundational aspects of data science, such as data representation, algorithmic fairness, and model interpretability, as well as cutting-edge applications in real-world scenarios. By bringing together experts in both theory and practice, we seek to address key issues that influence the future of data science, ultimately advancing its application to solve real-world problems.

Scope

The "Data Science: Foundations and Applications" session invites contributions that bridge the gap between foundational theories and practical implementations of data science. We encourage the submission of papers that focus on innovative algorithms, novel data representations, and emerging applications of data science in various domains. Topics of interest include, but are not limited to:

• Data science applications in healthcare, finance, marketing, and social sciences
• Machine learning and deep learning for complex data
• Data preprocessing and feature selection
• Core theories and algorithms
• Explaining and interpreting models
• Data-driven decisions
• Scalable algorithms for large datasets
• Transfer learning and adapting models to new domains
• Reinforcement learning and its real-world uses
• Human-computer interaction
• Data privacy and security in big data contexts

By providing a platform for discussing both theoretical advancements and real-world applications, this session aims to foster a deeper understanding of how data science can be leveraged to address critical challenges across diverse sectors.

Formatting Guidelines

We welcome English-language papers containing original and unpublished contributions to the fields of data mining and related areas. Manuscripts should adhere to the LNAI (Lecture Notes in Artificial Intelligence) format. For the template and detailed instructions on LNCS style, please refer to Springer's Author Instructions. Papers should adhere to the main conference guidelines, ensuring they do not exceed 15 pages in LNAI format. Submissions undergo a double-blind review process for ADMA2025. This means:

• Author identities and affiliations remain undisclosed to reviewers throughout the review process.
• Authors must prepare and submit blinded manuscripts that conceal author and affiliation information. Specific guidelines are outlined below.
• Both authors and reviewers are expected to make sincere efforts to prevent accidental de-blinding of any submission.
• All submitted papers must adhere to the following rules. Non-compliance may result in automatic rejection.

Submission Guidelines

Authors are invited to submit original research papers, case studies, and technical reports aligned with the theme of Data Science: Foundations and Applications. Submissions should adhere to the conference's formatting guidelines and be submitted through the CMT Submission System. All submissions will undergo a rigorous peer-review process to ensure quality and relevance. When submitting your manuscript, please choose the "Special Session Track" option and select the area of "3. Special Session: Data Science: Foundations and Applications."

Important Dates

• Paper Submission Deadline: 20th July, 2025 (AoE)
• Notification of Acceptance: 25th August, 2025 (AoE)
• Camera-Ready Paper Due: 1st September, 2025 (AoE)
• Conference Dates: 3rd~5th December, 2025 (AEST)

Session Chairs

• Chen Li, Osaka University, Japan
• Ye Zhu, Deakin University, Australian
• Huazhong Liu, Hainan University, China

Program Committee

• Yuncheng Jiang, South China Normal University, China
• Wenjun Ma, South China Normal University, China
• Liang Zhang, Lanzhou University, China
• Defeng Liu, Polytechnique Montréal, Canada
• Dongdong Wu, The University of Tokyo, Japan
• Zhiwen Zhou, Nagoya University, Japan
• Yinuo Ren, Stanford University, USA
• Longchao Da, Arizona State University, USA