4th International Conference on Data Mining, Big Data and Machine Learning (DBML 2026)
March 30 ~ 31, 2026, Virtual Conference
https://dbml2026.org/index
Scope &Topics
4th International Conference on Data Mining, Big Data and Machine Learning(DBML 2026) provides an excellent international forum for sharing knowledge and results in theory, methodology and applications of Data Mining, Big Data and Machine Learning.
Authors are solicited to contribute to the conference by submitting articles that illustrate research results, projects, surveying works and industrial experiences that describe significant advances in the following areas, but are not limited to:.
Topics of interest include, but are not limited to, the following Foundations of Data Mining & Machine Learning
- Theoretical foundations of ML and data mining
- Algorithms and models for large scale data analysis
- Optimization methods for ML
- Statistical and probabilistic modeling
- Causal inference and causal discovery
- Data centric AI and dataset engineering
- Benchmarking, evaluation, and reproducibility
Deep Learning, Representation Learning & Generative Models
- Deep learning architectures and methods
- Self supervised, semi supervised, and unsupervised learning
- Representation learning for structured and unstructured data
- Generative AI and foundation models
- Multimodal learning and cross domain integration
- Transfer learning, meta learning, and continual learning
- Reinforcement learning and sequential decision making
Big Data Systems, Platforms & Infrastructure
- Scalable, distributed, and parallel data mining
- Big data platforms, cloud, edge, and fog computing
- Big data management, indexing, and retrieval
- Real time analytics, stream processing, and event mining
- 5G/6G, networking, and distributed systems for big data
- High performance data processing systems
Mining Complex, Heterogeneous & High Dimensional Data
- Text, graph, temporal, spatial, and streaming data mining
- Web, social media, and multimedia mining
- Graph mining, network science, and graph neural networks
- Knowledge discovery and knowledge graphs
- Personalization, recommendation, and user modeling
- Visualization and human centered analytics
Trustworthy, Secure & Privacy Preserving Data Analytics
- Privacy preserving data mining and federated analytics
- Differential privacy, secure computation, and encryption
- Trustworthy, robust, and explainable ML
- Bias, fairness, and responsible data mining
- Big data security, governance, and compliance
- Adversarial ML and model robustness
Applications of Data Mining, Big Data & Machine Learning
- Bioinformatics, healthcare, and life sciences
- Finance, e commerce, and business intelligence
- Cybersecurity, fraud detection, and threat analytics
- IoT, smart cities, and sensor networks
- Climate, sustainability, and environmental analytics
- Industrial case studies and real world deployments
Paper Submission
Authors are invited to submit papers through the conference Submission System by February 21,2026. 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 nde conference will be published by International Journal on Cybernetics & Informatics (IJCI) (Confirmed).
Selected papers from DBML 2026, after further revisions, will be published in the special issue of the following journals