Prof. Tao Gu

Room 267, 4 Research Park Drive, North Ryde, NSW 2109, Australia
Phone: +61 2 9850 4357
tao.gu@mq.edu.au

  • Internet of Things
  • Embedded AI
  • Ubiquitous Computing
  • Mobile Computing
  • Wireless & Sensing
  • LPWANs

I am a Professor in the School of Computing. My research focuses on discovering innovative ways of sensing and connecting the physical world, and embedding AI intelligence to facilitate the building of new applications. I usually publish my work in top journals and conferences, including ACM/IEEE ToN, IEEE JSAC, IEEE TMC, MobiCom, SenSys, UbiComp, IPSN, and INFOCOM. Please visit my website at https://taogu.site/ for the specific research I am doing.

  • Internet of Things
  • Embedded AI
  • Ubiquitous Computing
  • Mobile Computing
  • Wireless & Sensing
  • LPWANs
  • Drone Remote Sensing
  • LoRa performance optimisation
  • mm-Wave Sensing for mobile health
  • Drone remote sensing for wildlife monitoring, search and rescue
  • On-device deep learning framework

Recent publications:

  1. Zihao Chu, Lei Xie, Tao Gu, Yanling Bu, Chuyu Wang, and Sanglu Lu. Edge-Eye: Rectifying Millimeter-Level Edge Deviation in Manufacturing using Camera-enabled IoT Edge Device, in Proc. of the 21st ACM/IEEE Conference on Information Processing in Sensor Networks (IPSN 2022), Milan, Italy, 4-6 May 2022.
  2. Jiuwu Zhang, Xiulong Liu, Tao Gu, Bojun Zhang, Dongdong Liu, Zijuan Liu, and Keqiu Li. An RFID and Computer Vision Fusion System for Book Inventory using Mobile Robot, in Proc. of IEEE INFOCOM 2022, May 2-5, 2022.
  3. Xiulong Liu, Dongdong Liu, Jiuwu Zhang, Tao Gu, and Keqiu Li. RFID and Camera Fusion for Recognition of Human-Object Interactions, in Proc. of the 27th International Conference on Mobile Computing and Neworking (MobiCom 2021), October 25-29, 2021.
  4. Xianjin Xia, Ningning Hou, Yuanqing Zheng, Tao Gu. PCube: Scaling LoRa Concurrent Transmissions with Reception Diversities, in Proc. of the 27th International Conference on Mobile Computing and Neworking (MobiCom 2021), October 25-29, 2021.
  5. Xianjin Xia, Yuanqing Zheng, and Tao Gu. FTrack: Parallel Decoding for LoRa Transmissions, IEEE/ACM Transactions on Networking (ToN), 2020.
  6. Yu Zhang, Tao Gu, and Xi Zhang. MDLdroidLite: a Release-and-Inhibit Control Approach to Resource-Efficient Deep Neural Networks on Mobile Devices, in Proc. of the 18th ACM Conference on Embedded Networked Sensor Systems (SenSys 2020), Yokohama, Japan, November 16-19, 2020.

Full publication list available at https://taogu.site/pub/