About Me
I am a 5-th year PhD candidate in Computer Engineering at Purdue University, advised by Prof. Y. Charlie Hu. My general research interest is in networked systems, mobile systems, and edge computing.
More recently, my research has focused on (1) Building efficient, high-throughput machine learning inference systems, with a focus on supporting latency-critical applications such as augmented reality (AR) and virtual reality (VR). (2) Experimental measurement studies on emerging mobile networks such as 5G mmWave. My research has been acknowledged with a Best Paper Award from ACM EdgeSys 2022, and a Best Dataset Award from PAM 2021.
Previously, I got my M.S. from the Dept. of Computer Science at UCLA in 2020, working with Prof. Lixia Zhang. I got a B.E. in Automation from Beihang University in 2018.
Recent Publications
High-Fidelity Cellular Network Control-Plane Traffic Generation without Domain Knowledge
ACM Internet Measurement Conference (IMC '24)
ARISE: High-Capacity AR Offloading Inference Serving via Proactive Scheduling
ACM International Conference on Mobile Systems, Applications, and Services (MobiSys '24)
Performance of Cellular Networks on the Wheels
ACM Internet Measurement Conference (IMC '23)
Can 5G mmWave Enable Edge-Assisted Real-Time Object Detection for Augmented Reality?
International Symposium on the Modeling, Analysis, and Simulation of Computer and Telecommunication Systems (MASCOTS '23)
AccuMO: Accuracy-Centric Multitask Offloading in Edge-Assisted Mobile Augmented Reality
Annual International Conference On Mobile Computing And Networking (MobiCom '23)