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Qiang Xu

Ph.D. Candidate
School of Electrical and Computer Engineering
Purdue University

I am a Ph.D. student in School of Electrical and Computer Engineering at Purdue University, supervised by Prof. Y. Charlie Hu. I am interested in mobile systems, edge computing, and their intersection with machine learning. My recent research focuses on building efficient machine learning inference systems for emerging applications like augmented reality. I received my B.E. in Computer Science and Technology from University of Science and Technology of China (USTC) in 2018.

I am actively seeking a position as a Research Scientist or Research Engineer. Please feel free to contact me if you are interested!

News

Feb 2023 I will be interning at NEC Labs this summer!
Nov 2022 AccuMO accepted to MobiCom 2023!
Jun 2022 Download our NextG-UP app to join us on a crowdsourced measurement study on the evolution of 5G.
Dec 2021 Our paper on energy impact of deep parameters accepted to SANER 2022!
Apr 2021 Our paper on energy-aware video streaming accepted to USENIX ATC 2021!

Publications

  1. Can 5G mmWave Enable Edge-Assisted Real-Time Object Detection for Augmented Reality?
    Moinak Ghoshal*, Z. Jonny Kong*, Qiang Xu*, Zixiao Lu, Shivang Aggarwal, Imran Khan, Jiayi Meng, Yuanjie Li, Y. Charlie Hu, and Dimitrios Koutsonikolas (* co-primary)
    31st International Symposium on the Modeling, Analysis, and Simulation of Computer and Telecommunication Systems (MASCOTS 2023)
  2. AccuMO: Accuracy-Centric Multitask Offloading in Edge-Assisted Mobile Augmented Reality
    Z. Jonny Kong*, Qiang Xu*, Jiayi Meng, and Y. Charlie Hu (* co-primary)
    The 29th Annual International Conference on Mobile Computing and Networking (MobiCom 2023)
  3. An In-Depth Study of Uplink Performance of 5G MmWave Networks
    Moinak Ghoshal*, Z. Jonny Kong*, Qiang Xu*, Zixiao Lu, Shivang Aggarwal, Imran Khan, Yuanjie Li, Y. Charlie Hu, and Dimitrios Koutsonikolas (* co-primary)
    The 2nd ACM SIGCOMM Workshop on 5G and Beyond Network Measurements, Modeling, and Use Cases (5G-MeMU 2022)
  4. Can 5G mmWave Support Multi-user AR?
    Moinak Ghoshal, Pranab Dash, Z. Jonny Kong, Qiang Xu, Y. Charlie Hu, Dimitrios Koutsonikolas, and Yuanjie Li
    Passive and Active Measurement Conference 2022 (PAM 2022)
  5. An Empirical Study on the Impact of Deep Parameters on Mobile App Energy Usage
    Qiang Xu, James C. Davis, Y. Charlie Hu, and Abhilash Jindal
    The 29th IEEE International Conference on Software Analysis, Evolution and Reengineering (SANER 2022)
  6. Do Larger (More Accurate) Deep Neural Network Models Help in Edge-Assisted Augmented Reality?
    Jiayi Meng, Z. Jonny Kong, Qiang Xu, and Y. Charlie Hu
    ACM SIGCOMM 2021 Workshop on Network-Application Integration (NAI 2021)
  7. Proactive Energy-Aware Adaptive Video Streaming on Mobile Devices
    Jiayi Meng, Qiang Xu, and Y. Charlie Hu
    2021 USENIX Annual Technical Conference (USENIX ATC 2021)