Machine Learning and Knowledge Extraction

Machine Learning and Knowledge Extraction publishes Special Issues to create collections of papers on specific topics, with the aim of building a community of authors and readers to discuss the latest research and develop new ideas and research directions. Special Issues are led by Guest Editors, who are experts on the topic and all Special Issue submissions follow MDPI's standard editorial process. The journal’s Editor-in-Chief and/or designated Editorial Board Member will oversee Guest Editor appointments and Special Issue proposals, checking their content for relevance and ensuring the suitability of the material for the journal. The papers published in a Special Issue will be collected and displayed on a dedicated page of the journal’s website. Further information on MDPI's Special Issue policies and Guest Editor responsibilities can be found here. For any inquiries related to a Special Issue, please contact the Editorial Office.

Section

Search by Title/Keyword

Order results

Display

Results per page

Using Large Language Models for Scientific Problem Solving and Engineering Design

edited by

Alex Doboli

, K. Wendy Tang and Simona Doboli

submission deadline 30 Apr 2026 | 5 articles | Viewed by 6208 | Submission Open

Keywords: large language models; problem solving; automated engineering design; agents; prompting; reinforcement learning; retrieval-augmented generation; symbolic machine learning; knowledge representations

(This special issue belongs to the Section Learning)

Language Acquisition and Understanding

edited by

Michal Ptaszynski

Rafal Rzepka

and Masaharu Yoshioka

submission deadline 15 Jul 2026 | 1 articles | Viewed by 1626 | Submission Open

Keywords: core concepts: language acquisition; language understanding; meaning representation; comprehension vs. generation; surface fluency vs. deep understanding; learning paradigms & methods: data-efficient learning; low-resource language learning; continual learning/lifelong learning; interactive learning; self-supervised learning; curriculum learning; cognitive & linguistic principles: compositionality/systematicity; generalization; child language development; cognitive science; psycholinguistics; symbolic reasoning; causality in language; embodiment & grounding: grounded language learning/language grounding; embodied AI/embodied agents; perception and language; language and action; multimodal learning; AI architectures & models: large language models (LLMs); foundation models; neuro-symbolic AI; agent-based models; emergent communication; evaluation & analysis: evaluation benchmarks; probing; interpretability/explainability; robustness; shortcut learning

Advancing Natural Language Processing for Low-Resource Languages and Dialects

edited by Tanjim Mahmud,

Michal Ptaszynski

and

Karl Andersson

submission deadline 31 Jul 2026 | 1 articles | Viewed by 1873 | Submission Open

Keywords: low-resource and dialect natural language processing; multilingual and crosslingual NLP; language resources and dataset creation; dialect and code-mixed language processing; NLP for underrepresented languages; machine learning and deep learning for NLP; linguistic and cultural adaptation in NLP; ethical and inclusive AI for language technologies

Trustworthy AI: Integrating Knowledge, Retrieval, and Reasoning

edited by

Konstantinos Diamantaras

submission deadline 31 Aug 2026 | 2 articles | Viewed by 543 | Submission Open

Keywords: trustworthy AI; knowledge graphs and ontologies; hallucination detection and mitigation; retrieval-augmented generation; modular and multi-agent systems

(This special issue belongs to the Section Learning)

Explainable Artificial Intelligence: Theoretical Foundations and Methodological Advances

edited by

Sheng Du

and

Javier Del Ser Lorente

submission deadline 31 Aug 2026 | Viewed by 282 | Submission Open

Keywords: symbolic explainability approaches granular computing Fuzzy logic Bayesian networks Probabilistic graphical models; explainable machine learning models Random forests Gradient boosting trees k-Nearest neighbors; XAI-based modelling for complex systems interpretable AI-enhanced adaptive control methodologies XAI-enabled intelligent optimization methodologies Knowledge graph-driven explainable AI methods; emerging explainable AI approaches neuro-symbolic explainable AI Federated explainable AI Large model explainable AI

(This special issue belongs to the Section Learning)

Clinically Robust and Transparent AI-Assisted Medical Diagnostics: From Learning Dynamics to Real-World Deployment

edited by

Milan Toma

and Constantinos Pattichis

submission deadline 30 Sep 2026 | Viewed by 112 | Submission Open

Keywords: machine learning evaluation in healthcare; learning dynamics of medical AI models; generalizability of diagnostic algorithms; robustness in clinical machine learning; predictive modeling for medical diagnostics; data-driven healthcare innovation; artificial intelligence for clinical decision support

(This special issue belongs to the Section Learning)

Artificial Intelligence for Signal, Image, and Multimodal Data Processing: Algorithms, Models, and Knowledge Extraction

edited by

Omneya A. Attallah

Sahar Selim

and

Lobna A. Said

submission deadline 15 Oct 2026 | Viewed by 247 | Submission Open

Keywords: signal processing; image processing; multimodal data; deep learning; multimodal fusion; foundation models; generative models; explainable methods; federated learning; cross-modal learning

(This special issue belongs to the Section Learning)

LLM-Inspired New Generation Machine Learning: Hyperparameter Optimization and Uncertainty Quantification

edited by

Vitaly Schetinin

Livija I. Jakaite

and

Jaroslaw Krzywanski

submission deadline 31 Dec 2026 | Viewed by 52 | Submission Open

Keywords: LLM-inspired ML; Bayesian learning methodology; hyperparameter optimization; uncertainty quantification; imbalanced data; survival analysis; financial forecasting

(This special issue belongs to the Section Learning)

Next-Generation TinyML: Innovations in Models, Security, and Applications for Constrained Intelligent Systems

edited by

Yassine Maleh

and

Khalid El Makkaoui

submission deadline 28 Feb 2027 | Viewed by 350 | Submission Open

Keywords: tiny machine learning; edge intelligence; model compression; tiny language models; resource-constrained AI; adversarial robustness; privacy-preserving machine learning; on-device inference; uncertainty quantification; federated learning

(This special issue belongs to the Section Safety, Security, Privacy, and Cyber Resilience)

Sustainable Applications for Machine Learning—2nd Edition

edited by

Danial Javaheri

Hassan Chizari

and

Amir Masoud Rahmani

submission deadline 31 Dec 2027 | Viewed by 246 | Submission Open

Keywords: machine learning; deep learning; artificial neural networks; reinforcement learning; sustainable computing; big data analytics; optimization; data mining

(This special issue belongs to the Section Learning)

Journal Menu

Journal Browser

Special Issues

Further Information

Guidelines

MDPI Initiatives

Follow MDPI