Innovations in Cloud Computing and Machine Learning Applications

A special issue of Mathematics (ISSN 2227-7390). This special issue belongs to the section "E1: Mathematics and Computer Science".

Deadline for manuscript submissions: 20 November 2025 | Viewed by 35

Special Issue Editors


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Guest Editor
Department of Computer Science, University of Michigan-Flint, Flint, MI 48502, USA
Interests: service computing; semantic web services; cloud computing; data mining; enterprise architecture

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Guest Editor
Department of Computer Science and Creative Technologies, University of the West of England, Frenchay, Bristol BS16 1QY, UK
Interests: malware analysis; ransomware research; mobile device security; cybersecurity; security of home automation and cloud; privacy and security; consultancy; security of Internet of Things (IoT); secure computer networks; network security

Special Issue Information

Dear Colleagues,

Cloud computing and machine learning are two key technologies shaping the future of computing and data processing. Cloud computing provides scalable and flexible access to computational resources, enabling efficient data storage and processing, while machine learning allows systems to uncover patterns and derive insights from huge datasets. Together, these technologies are being applied across a variety of fields, creating solutions that address complex challenges and improve operational efficiency.

This Special Issue focuses on exploring advancements and applications at the intersection of cloud computing and machine learning. It aims to highlight research and practical developments that demonstrate innovative uses, address challenges, and improve the integration of these technologies.

Topics of interest include, but are not limited to, the following:

  • Efficient deployment of machine learning models in cloud environments;
  • Resource allocation and optimization for machine learning workloads;
  • Data processing frameworks for large-scale machine learning in the cloud;
  • Security, privacy, and compliance in cloud-based systems;
  • Edge and cloud computing integration for distributed applications;
  • Real-time data analytics using cloud computing infrastructures;
  • Practical applications of cloud computing and machine learning in industries such as healthcare, finance, and logistics;
  • Cost-effective strategies for scaling machine learning operations in the cloud;
  • Case studies demonstrating the impact of cloud and machine learning technologies in real-world scenarios.

This Special Issue invites original research, reviews, and case studies that showcase the potential of combining cloud computing and machine learning. Contributions should emphasize practical approaches, technical challenges, and innovative solutions, providing valuable insights for researchers and practitioners alike.

Dr. Amal Alhosban
Dr. Abdullahi Arabo
Guest Editors

Manuscript Submission Information

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Keywords

  • cloud computing
  • machine learning
  • scalability
  • data processing
  • resource optimization
  • edge computing

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Published Papers

This special issue is now open for submission.
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