Zhuqi Li
Research Scientist at TikTok
[CV]
I am Zhuqi Li (click to get pronunciation), a Research Scientist at TikTok working on video upload and codec optimization.
I received my Ph.D. in Computer Science from Princeton University, advised by Professor Kyle Jamieson. My research focuses on cross-layer optimizations for video delivery on wireless network.
Experience
TikTok
2023/02 - Now
Research Scientist at TikTok
Princeton University
2017/08 - 2023/01
PhD student in Computer Science
Thesis: Cross-layer Optimization for Video Delivery on Wireless Networks
Facebook (Meta)
2021/06 - 2021/08
SWE Intern in Facebook Connectivity Lab
Peking University
2013/09 - 2017/07
B.S. (Summa Cum Laude) in Computer Science
Microsoft Research Asia
2016/04 - 2016/06 and 2016/09 - 2017/06
Research Intern in System and Algorithm Group
Carnegie Mellon University
2016/06 - 2016/09
Visiting Scholar in HCII
Projects
Dashlet
Advisor: Kyle Jamieson
Dashlet is a buffering system for short video streaming. Dashlet's algorithm leverages a model of users’ swipe statistics to determine the pre-buffering order and bitrate so that the user can have the best quality of experience when using short video apps.
Project Spider
Spider is an ultra high throughput, reliable relay wireless network infrastructure to support large scale video analytic applications. It supports high accuracy video analytics system with application-centric network design and optimization
Programmable Radio Environment
Advisor: Kyle Jamieson
Programmable Radio Environment (PRESS) is a project that focuses on facilitating wireless network with physical-layer programmability. We are seeking to answer two questions: how to endow the wireless channel with the maximum level of programmability; how to solve hard problems in wireless network with programmable radio environment.
Path-Guide
Advisor: Yuanchao Shu and Thomas Moscibroda
Path-Guide is a scalable navigation system, which uses peer to peer navigation as incentives to collect indoor traces and reconstructs the indoor trace map by concatenating different trace segments. Combining traditional signal processing and machine learning techniques, I designed a model to rearrange the segments in different traces and cast them into indoor maps. Based on this research, we developed a general commercial indoor navigation system, making indoor navigation see its future of getting wide development for the first time.
Publication
REITS: Reflective Surface for Intelligent Transportation Systems, HotMobile 2021
Zhuqi Li, Can Wu, Sigurd Wagner, James C. Sturm, Naveen Verma, and Kyle Jamieson
[Paper] [Media Coverage]
Incrementally-deployable Indoor Navigation with Automatic Trace Generation, IEEE INFOCOM 2019
Yuanchao Shu*, Zhuqi Li*, Börje F. Karlsson, Yiyong Lin, Thomas Moscibroda, and Kang G. Shin (* co-primary)
[Paper]
Population Distribution Projection by Modeling Geo Homophily in Online Social Networks, ICCSE 2017 (Best Paper Award)
Yuanxing Zhang, Zhuqi Li, Kaigui Bian, Yichong Bai, Zhi Yang, and Xiaoming Li
[PDF]
Demo: Towards Flexible and Scalable Indoor Navigation, ACM MobiCom 2017
Zhuqi Li, Yuanchao Shu, Börje F. Karlsson, Yiyong Lin, and Thomas Moscibroda
[PDF]
On Diffusion-restricted Social Network: A Measurement Study of WeChat Moments, IEEE ICC 2016
Look into My Eyes: Fine-grained Detection of Face-screen Distance on Smartphones, IEEE MSN 2016
Zhuqi Li, Weijie Chen, Zhenyi Li, and Kaigui Bian
[PDF]
Teaching
Introduction to Computer System (Peking University)
Teaching Assistant, Fall 2015
Advanced Computer Networks (Princeton University COS 561)
Teaching Assistant, Fall 2018
Advanced Programming Techniques (Princeton University COS 333)
Teaching Assistant, Spring 2020
Awards and Honors
© 2016