Data-oriented architecture survey published in ACM Computing Surveys
Christian Cabrera and colleagues publish the survey of how deployed machine learning systems follow data-oriented architecture, in ACM Computing Surveys.
Christian leads the Interfaces research programme at ML@CL. His work develops interpretable, self-sustaining multi-agent AI systems for real-world deployment, building on data-oriented architectures and the AutoAI project. Clinical validation includes the aICU partnership with Karolinska Institutet.
Proceedings of the 21st International Conference on Software Engineering for Adaptive and Self-Managing Systems (SEAMS 2026), :253-258
Third International Workshop on Large Language Models for Code (LLM4Code 2026), co-located with ICSE 2026, :
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ACM Computing Surveys, :
ACM Transactions on Software Engineering and Methodology, :