App Parameter Energy Profiling: Optimizing App Energy Drain by Finding Tunable App Parameters. - Qiang Xu 006; Y. Charlie Hu; Abhilash Jindal (CoRR, 2020)

Do Larger (More Accurate) Deep Neural Network Models Help in Edge-assisted Augmented Reality? - Jiayi Meng; Zhaoning Kong; Qiang Xu 006; Y. Charlie Hu (NAI@SIGCOMM, 2021)

Proactive Energy-Aware Adaptive Video Streaming on Mobile Devices. - Jiayi Meng; Qiang Xu 006; Y. Charlie Hu (USENIX ATC, 2021)

NextG-UP: a longitudinal and cross-sectional study of uplink performance of 5G networks. - Moinak Ghoshal; Imran Khan; Qiang Xu 006; Z. Jonny Kong; Y. Charlie Hu; Dimitrios Koutsonikolas (MobiCom, 2022)

NextG-up: a tool for measuring uplink performance of 5G networks. - Moinak Ghoshal; Imran Khan; Qiang Xu 006; Z. Jonny Kong; Y. Charlie Hu; Dimitrios Koutsonikolas (MobiSys, 2022)

Can 5G mmWave Support Multi-user AR? - Moinak Ghoshal; Pranab Dash; Zhaoning Kong; Qiang Xu 006; Y. Charlie Hu; Dimitrios Koutsonikolas; Yuanjie Li (PAM, 2022)

An in-depth study of uplink performance of 5G mmWave networks. - Moinak Ghoshal; Z. Jonny Kong; Qiang Xu 006; Zixiao Lu; Shivang Aggarwal; Imran Khan; Yuanjie Li; Y. Charlie Hu; Dimitrios Koutsonikolas (5G-MeMZ@SIGCOMM, 2022)

An Empirical Study on the Impact of Deep Parameters on Mobile App Energy Usage. - Qiang Xu 006; James C. Davis 001; Y. Charlie Hu; Abhilash Jindal (SANER, 2022)

Full results for paper "An Empirical Study on the Impact of Deep Parameters on Mobile App Energy Usage" (SANER 2022). - Qiang Xu 006; James C. Davis 001; Y. Charlie Hu; Abhilash Jindal (Zenodo, 2022)

Replication package for paper "An Empirical Study on the Impact of Deep Parameters on Mobile App Energy Usage" (SANER 2022). - Qiang Xu 006; James C. Davis 001; Y. Charlie Hu; Abhilash Jindal (Zenodo, 2022)

Can 5G mmWave Enable Edge-Assisted Real-Time Object Detection for Augmented Reality? - Moinak Ghoshal; Z. Jonny Kong; Qiang Xu 006; Zixiao Lu; Shivang Aggarwal; Imran Khan; Jiayi Meng; Yuanjie Li; Y. Charlie Hu; Dimitrios Koutsonikolas (MASCOTS, 2023)

AccuMO: Accuracy-Centric Multitask Offloading in Edge-Assisted Mobile Augmented Reality. - Z. Jonny Kong; Qiang Xu 006; Jiayi Meng; Y. Charlie Hu (MobiCom, 2023)

AccuMO: Accuracy-Centric Multitask Offloading in Edge-Assisted Mobile Augmented Reality. - Zhaoning Kong; Qiang Xu 006; Jiayi Meng; Y. Charlie Hu (Zenodo, 2023)

AccuMO: Accuracy-Centric Multitask Offloading in Edge-Assisted Mobile Augmented Reality. - Z. Jonny Kong; Qiang Xu 006; Jiayi Meng; Y. Charlie Hu (Zenodo, 2023)

ARISE: High-Capacity AR Offloading Inference Serving via Proactive Scheduling. - Z. Jonny Kong; Qiang Xu 006; Y. Charlie Hu (MobiSys, 2024)

PPipe: Efficient Video Analytics Serving on Heterogeneous GPU Clusters via Pool-Based Pipeline Parallelism. - Z. Jonny Kong; Qiang Xu 006; Y. Charlie Hu (USENIX ATC, 2025)

Dissecting the Impact of Mobile DVFS Governors on LLM Inference Performance and Energy Efficiency. - Zongpu Zhang; Pranab Dash; Y. Charlie Hu; Qiang Xu 006; Jian Li 021; Haibing Guan (CoRR, 2025)