
About
Christina Delimitrou is an Assistant Professor in the Electrical and Computer Engineering Department at Cornell University, where she leads the SAIL research group and is a member of the Computer Systems Laboratory (CSL). She holds the John and Norma Balen Sesquicentennial Faculty Fellowship and will join MIT EECS and CSAIL as a professor starting September 2022.
Dr. Delimitrou earned her Ph.D. and M.S. in Electrical Engineering from Stanford University, working with Christos Kozyrakis, and completed her undergraduate studies at the National Technical University of Athens. Her research focuses on computer architecture and systems, particularly on improving resource efficiency in large-scale datacenters through QoS-aware scheduling, resource management techniques, efficient server architectures, distributed performance debugging, and cloud security.
Her publication record demonstrates consistent high-impact research in datacenter systems, with recurring themes in microservices architecture, machine learning for systems, and QoS-aware resource management. Her work bridges theoretical computer architecture with practical cloud computing challenges, resulting in multiple IEEE Micro TopPicks awards and best paper recognitions at major architecture conferences.
Dr. Delimitrou has received numerous prestigious awards including:
- Sloan Research Fellowship in Computer Science
- NSF CAREER Award
- Microsoft Research Faculty Fellowship
- Intel Rising Star Award
- 2020 IEEE TCCA Young Computer Architect Award
- Multiple Google Faculty Research Awards
- Facebook Faculty Research Award
- Cornell Excellence in Research and Teaching Awards
She actively mentors PhD, MS, and undergraduate students in the SAIL research group, focusing on cloud computing and computer architecture. Her research has been supported by significant grants from NSF, Google, Microsoft, Facebook, and Intel. She teaches ECE5710: Datacenter Computing at Cornell, exploring hardware, systems software, and distributed systems technology in modern datacenters.
The SAIL research group develops innovative solutions for cloud infrastructure challenges, spanning from hardware acceleration to machine learning-driven resource management, with strong emphasis on practical implementation and real-world impact.
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