Machine Learning Systems
The Machine Learning Systems research area at ELIZA focuses on the engineering and design of efficient, scalable and robust systems for running and deploying machine learning models. This area bridges the gap between theoretical machine learning algorithms and their practical implementation in real-world applications. This research is essential for enabling the widespread adoption of AI technologies across diverse sectors and ensuring that machine learning innovations can deliver meaningful impact in production environments.
Key aspects explored within the Machine Learning Systems research area at ELIZA include:
- Development of new architecture and frameworks for machine learning, including the creation of innovative software and hardware infrastructure to efficiently support the training and inference of machine learning models.
- Investigating the scalability and efficiency of machine learning pipelines, particularly methods for handling large datasets and complex models, to ensure that machine learning systems can operate effectively in resource-constrained environments.
- Deployment and operationalisation of machine learning models, including research on how to deploy trained models in various applications and manage their performance and maintenance in production.
- Resource management and optimisation for machine learning workloads, involving study of how to effectively allocate and utilise computing resources (e.g., CPUs, GPUs) for training and inference.
- Assessing the reliability, robustness and security of machine learning systems to ensure that they are dependable, resilient to errors or attacks, and secure.
- Exploring hardware-aware machine learning to better understand how the underlying hardware architecture can be leveraged to improve the performance and efficiency of machine learning algorithms and systems.
Research in this area at ELIZA is vital for translating theoretical advances in machine learning into practical and impactful AI solutions. The findings contribute to building the necessary infrastructure and methodologies for the widespread adoption of AI across various domains.
Fellows of Machine Learning Systems
ELIZA empowers exceptional students to master the engineering behind machine learning systems. Our network connects you with leading researchers and industry experts across Germany, providing hands-on experience in building scalable, production-ready AI systems that bridge theory and real-world impact.
