About the Journal

                           Welcome to MLKD-2027

(Official website: https://mlkd.fikomdigi.unimus.ac.id/)

 

PMB UNIMUS

Transforming Data into Knowledge: Advancing Machine Learning Technologies for Smart and Sustainable Societies 

                           Semarang, Indonesia | 28-29 July, 2027

 

News

·       Website launched [30 July 2026]
·       Special issue journal proposals submitted [1 August 2026] 
·       Approved special sessions [1 August 2026] 
·       Proceedings proposal submitted to Springer Nature [6 August 2026]


The 2027 International Conference on Machine Learning and Knowledge Discovery (MLKD) is an international forum that brings together researchers, academicians, industry practitioners, and policymakers to exchange the latest advances in machine learning, artificial intelligence, data mining, knowledge discovery, and intelligent computing. The conference aims to foster collaboration between academia and industry by providing a platform for presenting original research, innovative methodologies, practical applications, and emerging trends that address real-world challenges across diverse domains.

MLKD focuses high-quality research contributions, case studies, industrial applications, and interdisciplinary works that advance the theory and practice of machine learning and knowledge discovery. The conference encourages discussions on novel algorithms, scalable intelligent systems, explainable AI, ethical AI, and data-driven decision-making to support sustainable digital transformation.

The conference also provides opportunities for networking, establishing research collaborations, and promoting knowledge transfer among participants from universities, research institutions, government agencies, and industry worldwide.

The conference particularly welcomes interdisciplinary research that combines machine learning, knowledge discovery, artificial intelligence, data science, and intelligent systems to solve complex scientific, engineering, business, healthcare, and societal challenges.