DMML 2026 - 7th International Conference on Data Mining & Machine Learning (DMML 2026)

Website https://bdbs2026.org/dmml/index | Edit Freely

Category Data Mining Foundations; Data Streams Mining; Graph Mining; Multimedia Data Mining; Parallel and Distributed Data Mining Algorithms; Pre-Processing Techniques; Security and Information Hiding in Data Mining; Spatial Data Mining; Text and Video Mining; Visualization; Web Mining; Data Mining Applications; Bioinformatics; Biometrics; Classification; Clustering; Databases; Educational Data Mining; Financial Modeling; Forecasting; Image Analysis; Social Networks; Knowledge Processing; Consistent Data Model; Consolidating and Explaining Discovered Knowledge; Data and Knowledge Representation; Evaluation; Exploratory Data Analysis; Pre- and Post-Processing; Inference of Causes; Integrating Constraints and Knowledge in the KDD Process; Integration of Data Warehousing; Interactive Data Exploration, Visualization and Discovery; Knowledge Discovery Framework and Process; Languages and Interfaces for Data Mining; Mining from Low-Quality Information Sources; Mining Trends, Opportunities and Risks; OLAP and Data Mining; Prediction; Statistical Techniques for Generating Robust Models; Machine Learning; Deep Learning; Learning in Knowledge-Intensive Systems; Learning Methods and Analysis; Learning Problems; Machine Learning Applications

Deadline: January 18, 2026 | Date: April 25, 2026-April 26, 2026

Venue/Country: Copenhagen, Denmark, Denmark

Updated: 2026-01-13 20:03:48 (GMT+9)

Call For Papers - CFP

April 25 ~ 26, 2026, Copenhagen, Denmark

https://bdbs2026.org/dmml/index

Call for Papers

7th International Conference on Data Mining & Machine Learning (DMML 2026) invites high quality research contributions from academia, industry, and government. As one of the leading global forums for presenting advances in data driven intelligence, DMML brings together researchers, practitioners, and innovators to exchange ideas, discuss emerging trends, and shape the future of data mining and machine learning.

Topics of interest include, but are not limited to, the following

Foundations of Data Mining & Machine Learning

Theoretical foundations of data mining

Statistical learning theory

Optimization methods for ML

Causality and causal discovery

Explainable and interpretable AI

Fairness, accountability, transparency, and ethics

Robust and trustworthy ML

Algorithms & Models

Classification, regression, and clustering

Ensemble learning and hybrid models

Deep learning architectures (CNNs, RNNs, Transformers, GNNs)

Graph mining and graph ML

Reinforcement learning

Probabilistic and Bayesian models

Transfer learning, domain adaptation, multi task learning

Online learning and data stream mining

Federated and privacy preserving learning

Large scale and distributed data mining algorithms

Data Processing & Engineering

Data cleaning, transformation, and pre processing

Feature engineering and feature selection

Data integration, fusion, and warehousing

ETL pipelines for ML systems

High performance and parallel computing

Edge, cloud, and distributed ML systems

Efficient model training, compression, and deployment

Knowledge Discovery & Pattern Mining

Frequent pattern and sequential pattern mining

Anomaly, outlier, and novelty detection

Temporal, spatial, and spatio temporal mining

Mining from incomplete or low quality data

Knowledge representation and reasoning

Knowledge graphs and semantic mining

Automated knowledge consolidation and explanation

Text, Language & Multimedia Mining

Natural language processing and text mining

Large language models and foundation models

Information retrieval and web mining

Social media and social network analysis

Image, video, and audio mining

Multimodal learning and cross media analysis

Generative models (GANs, diffusion models, multimodal generators)

Visualization, Interaction & Human Centered AI

Interactive data exploration and visual analytics

Human AI collaboration and human in the loop ML

Interfaces and languages for data mining

Visualization of complex models and explanations

User centered evaluation of ML systems

Security, Privacy & Responsible AI

Privacy preserving data mining (DP, MPC, FL)

Adversarial machine learning

Data security and information hiding

ML safety and risk assessment

Ethical and societal implications of AI

Applications of Data Mining & Machine Learning

Bioinformatics, genomics, and computational biology

Biometrics and identity recognition

Healthcare and medical imaging

Finance, forecasting, and risk modeling

Education and learning analytics

Smart cities, IoT, and sensor data mining

Cybersecurity and fraud detection

E commerce and recommendation systems

Climate science and environmental modeling

Industrial AI and predictive maintenance

Emerging Topics & Future Directions

Foundation models and general purpose AI

Autonomous systems and robotics

Quantum machine learning

Neuro symbolic AI

ML for scientific discovery

AI governance, policy, and global standards

Trends, opportunities, and risks in data mining & ML

Paper Submission

Authors are invited to submit papers through the conference Submission System by January 18, 2026. Submissions must be original and should not have been published previously or be under consideration for publication while being evaluated for this conference. The proceedings of the conference will be published by The proceedings of the conference will be published by Computer Science Conference Proceedings in Computer Science & Information Technology (CS & IT) series (Confirmed).

Selected papers from DMML 2026, after further revisions, will be published in the special issue of the following journals.

• International Journal of Multimedia & Its Applications (IJMA) -

• International Journal of Data Mining & Knowledge Management Process (IJDKP)

• International Journal of Database Management Systems (IJDMS)- WJCI, Indexed

• Machine Learning and Applications: An International Journal (MLAIJ)

• International Journal of Web & Semantic Technology (IJWesT)

• Advances in Vision Computing: An International Journal (AVC)

Important Dates

• Submission Deadline: January 18, 2026

• Authors Notification: March 14, 2026

• Registration & camera - Ready Paper Due: March 21, 2026

Contact Us

Here's where you can reach us: dmmlbdbs2026.org (or) dmmlconfeeyahoo.com