Tao Gu

Tao Gu

Email: firstname dot lastname AT mq.edu.au
Phone: +61-2-9850-4357
Address: Room 267, 4 Research Park Drive, North Ryde, NSW 2109, Australia

School of Computing, Macquarie University

I am currently a Professor in School of Computing at Macquarie University, Sydney. I obtained my Ph.D. in Computer Science from National University of Singapore, M.Sc. in Electrical and Electronic Engineering from Nanyang Technological University, and B.Eng. in Automatic Control from Huazhong University of Science and Technology. I have served as an Editor of Proc. of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies (IMWUT), an Associate Editor of IEEE Transactions on Mobile Computing (TMC) and IEEE Internet of Things Journal (IoT-J).

The long-term goal of my research aims to discover innovative ways of connecting and sensing the physical world, and embedding AI intelligence to facilitate the development of new computing systems and applications. My current research interests include Internet of Things, Embedded AI, Mobile Computing, Ubiquitous Computing, and Big Data Analytics. Please visit the Projects page for the specific research we are doing. We usually publish our work in journals and conferences, including MobiCom, MobiSys, SenSys, UbiComp, IPSN, and INFOCOM.

We are hiring multiple PhD students! Please see Hiring.

Research Projects

Critical Supply Chain CRC

Critical Supply Chain CRC will deliver an innovation ecosystem supporting Australia’s economic future through effective and highly competitive domestic and export supply chains. It is critical that all stakeholders come together to provide demand led end-to-end supply chain solutions.

Sensing for Digital Health

Contactless vital sign and health monitoring, non-invasive monitoring of blood pressure, sleep stage, heartbeat, and respiration for digital health applications.

[MobiSys'23] Lei Wang, Tao Gu, Wei Li, Haipeng Dai, Yong Zhang, Dongxiao Yu, Chenren Xu, and Daqing Zhang. DFSense: Dual Forming based Multi-user Acoustic Sensing for Heartbeat Monitoring, in Proc. of the 21st ACM International Conference on Mobile Systems, Applications, and Services (MobiSys 2023), Helsinki, Finland, June 18-22, 2023.
[SenSys'22] Zhenguo Shi, Tao Gu, Yu Zhang, and Xi Zhang. mmBP: Contact-free Millimetre-wave Radar based Approach to Blood Pressure Measurement, in Proc. of the 20th ACM Conference on Embedded Networked Sensor Systems (SenSys 2022), Boston, United States, November 6-9, 2022. [Demo Video]
[UbiComp'22] Lei Wang, Wei Li, Ke Sun, Fusang Zhang, Tao Gu, Chenren Xu, and Daqing Zhang. LoEar: Push the Range Limit of Acoustic Sensing for Vital Sign Monitoring, the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies (IMWUT), 2022.
[UbiComp'21] Jinyi Liu, Youwei Zeng, Tao Gu, Leye Wang, and Daqing Zhang. WiPhone: Smartphone-based Respiration Monitoring using Ambient Reflected WiFi Signals, the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies (IMWUT), 2021.

Sensing and Mobile Systems

New sensors, algorithms, and mobile systems that enable ubiquitous sensing, improve security, and build the Internet of Things.

[MobiCom'23] Xi Zhang*, Yu Zhang*, Zhenguo Shi, and Tao Gu. mmFER: Millimetre-wave Radar based Facial Expression Recognition for Multimedia IoT Applications, in Proc. of the 29th International Conference on Mobile Computing and Networking (MobiCom 2023), Madrid, Spain, October 2-6, 2023. (* Equal Contribution)
[MobiCom'22] Yao Wang, Tao Gu, Yu Zhang, Minjie Lyu, Tom H. Luan, and Hui Li. Enabling Secure Touch-to-Access Device Pairing based on Human Body's Electrical Response, in Proc. of the 28th International Conference on Mobile Computing and Neworking (MobiCom 2022), Sydney, Australia, October 17-21, 2022. [Demo Video]
[IPSN'22] 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.
[MobiCom'21] 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.

LoRaWANs

New transmission techniqes, energy saving approaches, and network frameworks that enable low-cost long-range LoRa networks, optimize communications, and enhance network security.

[IPSN'23] Zehua Sun, Tao Ni, Huanqi Yang, Kai Liu, Yu Zhang, Tao Gu, and Weitao Xu. FLoRa: Energy-Efficient, Reliable, and Beamforming-Assisted Over-The-Air Firmware Update in LoRa Networks, in Proc. of the 22nd ACM/IEEE Conference on Information Processing in Sensor Networks (IPSN 2023), San Antonio, Texas, May 9-12, 2023.
[INFOCOM'23] Huanqi Yang, Zehua Sun, Hongbo Liu, Xianjin Xia, Yu Zhang, Tao Gu, Gerhard Hancke, and Weitao Xu. ChirpKey: A Chirp-level Information-based Key Generation Scheme for LoRa Networks via Perturbed Compressed Sensing, in Proc. of IEEE INFOCOM 2023, New York area, USA, May 17-20, 2023.
[MobiCom'21] 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.
[INFOCOM'20] Xianjin Xia, Yuanqing Zheng, and Tao Gu. LiteNap: Downclocking LoRa Reception, in Proc. of IEEE INFOCOM 2020, Toronto, Canada, July 6-9, 2020.

Edge and Embedded AI

New learning frameworks, lightweight designs, and end-to-end optimization that enpower edge computing, advance embedded systems, and facilitate on-device AI applications.

[ToN'21] Yu Zhang, Tao Gu, and Xi Zhang. MDLdroid: a ChainSGD-reduce Approach to Mobile Deep Learning for Personal Mobile Sensing, IEEE/ACM Transactions on Networking (ToN), 2021.
[TMC'21] Yu Zhang, Tao Gu, and Xi Zhang. MDLdroidLite: a Release-and-Inhibit Control Approach to Resource-Efficient Deep Neural Networks on Mobile Devices, IEEE Transactions on Mobile Computing (TMC), 2021.
[SenSys'20] 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. [Demo Video]
[IPSN'20] Yu Zhang, Tao Gu, and Xi Zhang. MDLdroid: a ChainSGD-reduce Approach to Mobile Deep Learning for Personal Mobile Sensing, in Proc. of the 19th ACM/IEEE Conference on Information Processing in Sensor Networks (IPSN 2020), Sydney, Australia, April 21-24, 2020.

Drone Systems

New autonomous designs, remote sensing techniques, and communications that enhance roubstness, stafy, and reilability.