7th International Conference on Machine Learning Techniques and Data Science (MLDS 2026)
September 19 ~ 20, 2026, Copenhagen, Denmark
Scope & Topics 7th International Conference on Machine Learning Techniques and Data Science (MLDS 2026) offers a premier international forum for researchers, practitioners, and industry experts to present and discuss the latest innovations in machine learning, artificial intelligence, and data science. As these fields continue to evolve rapidly, MLDS 2026 aims to bring together cutting edge research that shapes the future of intelligent technologies and data driven decision making.
MLDS 2026 encourages submissions that explore theoretical foundations, novel algorithms, scalable systems, and impactful applications across diverse domains. The conference welcomes research articles, experimental studies, survey papers, and industrial case studies that demonstrate significant progress in machine learning techniques, data science methodologies, and real world deployments.
Authors are invited to contribute original work that illustrates research results, innovative projects, comprehensive surveys, and practical industrial experiences. Submissions may address, but are not limited to, the topics listed.
Topics of interest include, but are not limited to, the following - Machine learning theory and foundations
- Deep learning architectures, transformers and optimization
- Representation learning and self supervised learning
- Large language models (LLMs) and foundation models
- Multimodal foundation models (vision language audio)
- Generative AI: diffusion, transformers and multimodal generation
- Retrieval augmented generation (RAG) and knowledge grounded ML
- Learning in knowledge intensive systems
- Reinforcement learning, decision making and sequential agents
- Graph machine learning and network representation learning
- Hybrid ML systems and neuro symbolic AI
- Automated machine learning (AutoML) and hyperparameter optimization
- Explainable AI (XAI), interpretability and model transparency
- AI safety, alignment and responsible AI
- Frontier AI risk, evaluation and governance
- Fairness, accountability and trustworthy ML
- Adversarial ML, robustness, poisoning and model extraction
- Federated learning, privacy preserving ML and secure aggregation
- ML for edge, mobile and resource constrained devices
- Distributed ML, parallel training and systems for LLMs
- ML systems, MLOps and scalable training infrastructure
- Machine learning applications across domains
- ML for healthcare, genomics and medical imaging
- ML for scientific discovery, simulation and surrogate modeling
- ML for climate science, sustainability and environmental modeling
- ML for cybersecurity, threat intelligence and automated defense
- ML for robotics, embodied AI and interactive agents
- Recommender systems and personalization
- Natural language processing and instruction tuned models
- Computer vision, multimodal learning and perception
- Speech processing, audio intelligence and spoken language models
- Time series forecasting, sequential modeling and anomaly detection
- Social network analysis, graph mining and influence modeling
- Data science theory, pipelines and workflow automation
- Data centric AI, data quality optimization and dataset distillation
- Big data analytics and large scale data processing
- Business analytics, decision intelligence and applied DS
- Data engineering, data management and data quality
- Databases, query optimization and modern data systems
- Knowledge discovery, pattern mining and advanced data mining
- Causal inference, causal ML and counterfactual reasoning
- Synthetic data, simulation based generation and digital twins
- ML for finance, economics and market modeling
- Ethical, societal and policy implications of ML/DS
Paper Submission Authors are invited to submit papers through the conference Submission System by July 04, 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 Computer Science Conference Proceedings in Computer Science & Information Technology (CS & IT) series (Confirmed). Selected papers from MLDS 2026, after further revisions, will be published in the special issue of the following journals. Important Dates | Submission Deadline | : | July 04, 2026 | | Authors Notification | : | July 25, 2026 | | Final Manuscript Due | : | August 01, 2026 |
Co - Located Event ***** The invited talk proposals can be submitted to mlds@nlai2026.org |
