EASL
Efficient Architectures and Systems Lab (EASL)
We design and build computer systems for large-scale applications, such as cloud computing services, data analytics, and machine learning. We aim to improve the performance and resource efficiency of cloud computing while making it easier for users to deploy and manage their applications. Our research work spans operating systems, computer architecture, and their intersection with machine learning.
Research Focus Areas
EASL Group Members:
Faculty:
PhD Students:
- Tom Kuchler
- Lazar Cvetković
- external page Foteini Strati
- external page Maximilian Böther
- external page Xiaozhe Yao
- external page Mihajlo Djokic
- external page Dan Graur (primary advisor: Prof. Gustavo Alonso)
- external page Dimitris Koutsoukos (primary advisor: Prof. Gustavo Alonso)
Post-docs:
Masters students:
- external page François Costa
- external page Ixeia Sánchez Périz
- external page Pinghe Li
- external page Jingyi Zhu
- external page Paul Elvinger
- external page Xianzhe Ma
- external page Fangyun Lin
- external page Victor Vitez
Bachelor students: