Short Bio

I am currently a 3rd year Phd student in Computer Science Department at Dartmouth College, under supervision of Prof. Xia Zhou in DartNets Lab. I received my B.E. in Computer Science and B.A. in Digital Art Design in 2012 at Tsinghua University. I also earned my M.S. in 2015 at Tsinghua University.
My research interests lie in mobile system and wireless networking.

Publications

  • Customizing Indoor Wireless Coverage via 3D-Fabricated Reflectors.[PDF][Project website]
    Xi Xiong, Justin Chan, Ethan Yu, Nisha Kumari, Ardalan Amiri Sani, Changxi Zheng, Xia Zhou.
  • Reconstructing Hand Poses Using Visible Light.[PDF][Video] [Project website]
    Tianxing Li (co-primary), Xi Xiong (co-primary), Yifei Xie, George Hito, Xing-Dong Yang, and Xia Zhou.
  • Position: Augmenting Inertial Tracking with Light.[PDF]
    Zhao Tian, Yulin Wei, Xi Xiong, Weinin Chang, Hsinmu Tsai, Kate Chingju Lin, Changxi Zheng, and Xia Zhou.
  • Automating 3D Wireless Measurements with Drones.[PDF][Video]
    Ethan Yu, Xi Xiong, and Xia Zhou.
  • SmartGuide: Towards Single-image Building Localization with Smartphone.[PDF]
    Xi Xiong, Zheng Yang, Longfei Shangguan, Yun Fei, Milos Stojmenovic, and Yunhao Liu.
  • GF(2^n) bit-parallel squarer using generalised polynomial basis for new class of irreducible pentanomials. [PDF]
    Xi Xiong, Haining Fan.
  • GF(2^n) redundant representation using matrix embedding for irreducible trinomials. [PDF]
    Yongjia Wang, Xi Xiong, Haining Fan.

Research

SmartGuide

Building Localization via One Smartphone's Photo

SmartGuide is a mobile service on localizing a distant unknown building by taking one photo of it. It detects user's shooting position and shooting direction by recording data of GPS, accelerometer, magnetic sensor. Based on Manhattan World Assumption, some structure information of the target building can be inferred from the photo. At last, we identify the target building on a local Google Map based on above features.

iNav

Microsoft Research Asia

iNav aims to generate crowdsourcing semantic maps via rich mobile contextual information and path-based check-ins. Meanwhile, it provides indoor localization service based on crowdsourced maps. The team is composed of researchers from Mobile and Sensing Systems Group, software engineers from Innovation Engineering Group, and UI designers from Human Computer Interaction Group. I was responsible for developing iNav client on Android and improving map crowdsourcing algorithm.