Scalable Computing Systems Laboratory
Beyond the AI algorithms and the availability of large volume of data, this is now possible because we can scale systems to thousand, even millions of distributed entities. Yet, designing efficient distributed systems come with many challenges that we address in our team.
We are interested in all aspects of such large-scale distributed systems be they datacenters, edge computing, fully decentralized systems, self organizing systems, and we are working on scalable design, failure resilience, performance and privacy-preservation.
Our current research interests include:
System support for machine learning
Federated Learning Systems
Privacy-aware recommendation systems