About Me
I am a 5-th year computer systems PhD at Purdue University, advised by Prof. Y. Charlie Hu.
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
PPIPE: Efficient Video Analytics Serving on Heterogeneous GPU Clusters via Pool-Based Pipeline Parallelism
2025 USENIX Annual Technical Conference (ATC '25)
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)
AccuMO: Accuracy-Centric Multitask Offloading in Edge-Assisted Mobile Augmented Reality
Annual International Conference On Mobile Computing And Networking (MobiCom '23)