zhuqil [at] cs [dot] princeton [dot] edu
35 Olden Street, Princeton, NJ
(+1) 609 - 3757 - 506
2017/08 - Now
PhD student in Computer Science
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
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.
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
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.
Advisor: Jason Hong
Urban Analytics is a project that evaluates the neighborhoods of a city by analyzing geo-tagged tweets. By combining analysis on both topic and sentiment domain, I was able to extract the features of different neighborhood in Pittsburgh.
Towards Programming the Radio Environment with Large Arrays of Inexpensive Antennas, NSDI 2019
Zhuqi Li, Yaxiong Xie, Longfei Shangguan, Rotman Ivan Zelaya, Jeremy Gummeson, Wenjun Hu, and Kyle Jamieson
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)