Ph.D., Massachusetts Institute of Technology, 2018
Interests: Systems, networking, distributed systems
Ravi Netravali is an Assistant Professor in the Computer Science Department at Princeton University. His research interests are broadly in computer systems and networking, with a focus on building practical systems to improve the performance and debugging of large-scale, distributed applications for both end users and developers. His research has been recognized with an NSF CAREER Award, a Google Faculty Research Award, an ACM SoCC Best Paper Award, and an IRTF Applied Networking Research Prize. Prior to joining Princeton, Netravali was an Assistant Professor of Computer Science at UCLA from 2019-2021. He received his PhD in Computer Science from MIT in 2018, and a BS in Electrical Engineering from Columbia University in 2012.
- "Reducto: On-Camera Filtering for Resource-Efficient Real-Time Video Analytics." Yuanqi Li, Arthi Padmanabhan, Pengzhan Zhao, Yufei Wang, Guoqing Harry Xu, and Ravi Netravali. ACM SIGCOMM 2020.
- "Fawkes: Faster Mobile Page Loads via App-Inspired Static Templating." Shaghayegh Mardani, Mayank Singh, and Ravi Netravali. USENIX NSDI 2020.
- "Continuous Prefetch for Interactive Data Applications." Haneen Mohammed, Ziyun Wei, Eugene Wu, and Ravi Netravali. VLDB 2020.
- "Neural Adaptive Video Streaming with Pensieve." Hongzi Mao, Ravi Netravali, and Mohammad Alizadeh. ACM SIGCOMM 2017.
- "Polaris: Faster Page Loads Using Fine-grained Dependency Tracking." Ravi Netravali, Ameesh Goyal, James Mickens, and Hari Balakrishnan. USENIX NSDI 2016.