call for papers - MLDS 2026

7th International Conference on Machine Learning Techniques and Data Science

(MLDS 2026)

September 19 ~ 20, 2026, Copenhagen, Denmark

https://nlai2026.org/mlds/index

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 August

15, 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.

 International Journal of Artificial Intelligence & Applications (IJAIA)

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

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

 International Journal of Database Management System (IJDMS)

 Information Technology in Industry (ITII)

Important Dates

 Submission Deadline: August 15, 2026

 Authors Notification: August 25, 2026

 Registration & Camera-Ready Paper Due: September 01, 2026

Contact Us

Here's where you can reach us : mlds@nlai2026.org (or) confmlds@gmail.com

Submission System Link: https://iccsea2026.org/submission/index.php

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