The Interdisciplinary Data Science Conference 2025, formaly International Data Science Conference, invites researchers, practitioners, and industry experts to submit their latest findings and innovations in the field of Data Science. This conference aims to foster interdisciplinary collaboration, share cutting-edge research, and explore the diverse applications of data science across various domains. We seek to create a balanced and comprehensive platform that highlights foundational data management, statistical analysis, practical applications, and innovative advancements in machine learning and artificial intelligence.

For Submission of research papers, you can find underneath the topics.
If you are interested in submitting Industry Contributions and Workshop Proposals please find more details on the our website .

Submissions are welcome
with the following topics to cover a broad spectrum within Data Science, ensuring a balanced representation across different areas of expertise.

Statistical Methods and Traditional Data Analysis

Time Series Analysis
Multivariate Time Series: Anomaly detection, Generative models
Time Series Forecasting and Prediction techniques
Exploratory Data Analysis (EDA)
Effective data visualization strategies
Descriptive statistics for data interpretation
Advanced Statistical Modeling
Regression and Classification methods
Bayesian statistics applications

Machine Learning and AI

Core Machine Learning Methods
Supervised and Unsupervised Learning algorithms
Transfer Learning, Incremental and Adaptive Learning
Specialized AI Techniques
Reinforcement Learning and Control Theory
Topological Data Analysis and Topological Machine Learning
Alternative Machine Learning Models beyond neural networks
Imaging and Computer Vision
Deep Learning applications in medical imaging
Representation Learning and Feature Engineering
Feature extraction and representation methods

Security, Privacy, and Ethical Considerations

Security and Privacy for AI
Adversarial AI and Countermeasures
Explainable AI for Security
Deep Fake Detection across various data types
Robustness of AI Methods against disruptions and attacks
Ethical and Legislative Aspects
Ethical issues in AI development and application
Analysis of the EU AI Act and its implications

Data Science in Industry and Production

MLOps and Data Engineering
MLOps strategies for industrial and Operational Technology (OT) contexts
Building efficient data pipelines and workflow automation
Co-Simulation and Interdisciplinary Applications
Integrating reinforcement learning with co-simulation techniques
Dynamic Systems and Control
Modeling and controlling dynamic systems using machine learning

Emerging and Interdisciplinary Topics

Semantic Technologies
Knowledge Graphs and Semantic Inference
Semantic Information Modeling in industrial contexts
Topical Innovations
Advanced Topological Data Analysis methods
Incremental and Adaptive Learning techniques
Collaborative and Open Research
Promoting open data and collaborative research efforts
Encouraging interdisciplinary projects across multiple domains

Data Management and Infrastructure

Data Governance and Sovereignty
Gaia-X – Data Spaces and Data Sovereignty
Ensuring data sovereignty and compliance with data protection regulations
Public Data Science and Open Data
Open Data Initiatives
Management of public data by governmental bodies
Data-driven Business Models
Leveraging data as a central resource in business
Data-driven decision-making and innovation case studies
Data Privacy and Security
Privacy and Security for Federated Learning
General data security practices across platforms

How to submit
Papers must be clearly presented in English language and must not exceed 14 pages, including tables, figures, references, and appendices. Submissions which are simultaneously submitted to this conference and other events or publication venues as well as submissions that do not utilize the correct formatting template, will be automatically rejected. Submissions will be selected based on their originality, timeliness, significance, relevance, and clarity of presentation. Submissions should be regarded as a commitment that, should the paper be accepted, at least one of the authors has to register and attend the conference to present the work (on site or online). Accepted and presented papers will be included in the iDSC proceedings. Reviews are double-blind.

Regarding the preparation of submissions, please use either the provided Word or LaTeX template from the website under Call for papers.

Attention: Please ensure that your submissions are ready for the double-blind review process and therefore do not contain any information, which could disclose the identity of the authors, such as author names, acknowledgements etc.

Submission will be handled by Online Conference Service OCS - Springer.

https://ocs.springer.com/misc/home/Research_Track_iDSC2025