Christos Antonopoulos of UTH presented the MLSysOps Project at Data Week 2025 during the session “MLOps, Continuous Learning, and Resource Management in the Edge-Cloud Continuum“. His talk, titled “ML-based Autonomic System Management in the Edge-Cloud Continuum” emphasized the project’s contributions to ML-based automated resource management, resource-aware workload deployment, and the ML-assisted orchestration of complex application workflows.

Following the presentations, Christos Antonopoulos participated in a panel alongside experts from academia and industry. The discussion explored the practical challenges of integrating ML-driven methods into production environments, including the interfacing with legacy infrastructure, the availability and annotation of training data, and the deployment of resilient MLOps pipelines across the edge-cloud continuum. Christos contributed insights from the MLSysOps project’s ongoing efforts to build dependable and intelligent systems at the edge-cloud frontier, driven by the requirements of real-world applications.