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.
Biography
Andrei is a visiting researcher with the interfaces project. He completed his PhD at ML@CL in 2024 and is now Chief Engineer at Pasteur Labs. His research focus is the intersection of software systems and machine learning. Prior to coming to Cambridge, he received a Masters degree from Belarusian State University, and spent a number of years as a software engineer, working on everything from web applications to data center networks.
Links
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24 September 2025
27 February 2023
New survey on adoption of data-oriented architecture
A new survey from the ML@CL group explores adoption of Data-Oriented Architecture paradigm for ML deployment.
17 May 2022
AutoAI research published at CAIN 2022
The AutoAI team will present new research on flow-based programming in the context of machine learning deployment at the first International Conference on AI Engineering.
Publications
Machine Learning Systems: A Survey from a Data-Oriented Perspective
ACM Computing Surveys, :
An Empirical Evaluation of Flow Based Programming in the Machine Learning Deployment Context
1st International Conference on AI Engineering – Software Engineering for AI, :
Challenges in Machine Learning Deployment: A Survey of Case Studies
ACM Comput. Surv., Association for Computing Machinery:
Towards Better Data Discovery and Collection with Flow-Based Programming
Neurips Data-Centric AI Workshop (DCAI), :