Bio
Hi, my name is Zhenyu Song (宋振宇, pronounced as zen-u). I am an Applied Scientist at AWS AI Labs, working on systems for large language models.
I obtained my Ph.D. degree from Princeton CS Department, under the supervision of Prof. Kai Li and Prof. Wyatt Lloyd, where I worked on using machine learning to improve content delivery network (CDN) caching.
Email: zhenyus [at] cs.princeton.edu
Publications
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HALP: Heuristic Aided Learned Preference Eviction Policy for YouTube Content Delivery Network. [PDF] [Video]
Zhenyu Song, Kevin Chen, Nikhil Sarda, Deniz Altınbüken, Eugene Brevdo, Jimmy Coleman, Xiao Ju, Pawel Jurczyk, Richard Schooler, Ramki Gummadi.
NSDI 2023 -
Learning Relaxed Belady for Content Distribution Network Caching. [PDF] [Code] [Dataset] [Video]
Zhenyu Song, Daniel S. Berger, Kai Li, Wyatt Lloyd.
NSDI 2020 -
Wi-Fi Goes to Town: Rapid Picocell Switching for Wireless Transit Networks. [PDF] [Slides] [Video] [Demo]
Zhenyu Song, Longfei Shangguan, Kyle Jamieson.
SIGCOMM 2017 -
Modeling Topic-level Academic Influence in Scientific Literatures. [PDF][Slides]
Jiaming Shen, Zhenyu Song, Shitao Li, Zhaowei Tan, Yuning Mao, Luoyi Fu, Li Song, Xinbing Wang.
AAAI 2016 Workshop on Scholarly Big Data -
HiQuadLoc: A RSS Fingerprinting based Indoor Localization System for Quadrotors. [PDF]
Xiaohua Tian, Zhenyu Song, Binyao Jiang, Yang Zhang, Tuo Yu, Xinbing Wang.
IEEE TMC 2016
Collaborators
My research has been made possible through collaborations with several incredible mentors and mentees.
Mentors
Mentees
- Maxwell Xu (Princeton Undergrad 2021) → Microsoft
- Audrey Cheng (Princeton Undergrad 2020) → Berkeley PhD Program
- John Suh (Princeton Undergrad 2020) → Robinhood
Service
External Reviewer
- OSDI 2022
- OSDI 2018