Call for Papers: Special Issue on MLOps – Bridging the Gap Between Machine Learning and Operations

IEEE Software seeks submissions for this upcoming special issue.
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Submissions Due: 7 March 2024

Important Dates

  • Submission date: 7 March 2024

Publication: November/December 2024

The rapid advancement of machine learning (ML) algorithms and the increasing demand for deploying ML models in real-world applications have highlighted the critical need for effective Machine Learning Operations (MLOps). MLOps encompasses the practices, methodologies, and tools required to streamline and automate the lifecycle management of ML models, ensuring their efficient development, deployment, monitoring, and maintenance. 

We invite researchers, practitioners, and industry experts to submit their original contributions to IEEE Software Special Issue on MLOps. The special issue aims to bring together professionals from academia and industry to explore the latest advancements, challenges, and solutions in the field of MLOps. We welcome papers that cover a wide range of topics, including but not limited to: 

  • MLOps frameworks and architectures 
  • Continuous integration and delivery of ML models 
  • Scalable and efficient ML model deployment 
  • Monitoring and logging for ML systems 
  • Model versioning and reproducibility 
  • Data management and governance for ML pipelines 
  • Performance optimization and resource allocation in ML systems 
  • Security and privacy in MLOps 
  • Explainability and interpretability of ML models in production 
  • MLOps Auditing 
  • Collaboration and DevOps practices in ML projects 
  • Real-world case studies and best practices in MLOps 
  • MLOps for specific domains or IT enterprise (e.g., healthcare, finance, manufacturing) 
  • Regulatory and Policy Aspects of MLOps 
  • MLOps at Scale 
  • LLMOps – Machine Learning and Operations for Large Language Models ● Responsible AI in MLOps or in AI or ML-based systems 
  • Bias and Fairness in MLOps or in AI or ML-based systems 
  • Ethics in MLOps or in AI or ML-based systems 
  • Human-Aspects in MLOps or in AI or ML-based systems 
  • MLOps in Education 
  • MLOps Tools and Open-Source Ecosystem

Submission Guidelines

Manuscripts must not exceed 4,200 words, including figures and tables, which count for 250 words each. Submissions in excess of these limits may be rejected without refereeing. The articles we deem within the theme and scope will be peer reviewed and are subject to editing for magazine style, clarity, organization, and space. Be sure to include the name of the theme you’re submitting for. Articles should have a practical orientation and be written in a style accessible to practitioners. Overly complex, purely research-oriented, or highly theoretical aren’t appropriate, however articles providing scientific evidence are welcome if they focus on practical and industrial contexts. IEEE Software doesn’t republish material published previously in other venues, including other periodicals and formal conference or workshop proceedings, whether previous publication was in print or electronic form.



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