Dr. Zhongqin WangI specialize in designing Contactless, Sensorless, and Wireless sensing
solutions that extend beyond traditional visual systems, aiming to build innovative and
commercially viable sensing applications.
Email:
zhongqin.wang@uts.edu.au
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RESEARCH INTERESTS
- Radio Sensing and Communication: Integrating sensing and communication to harness radio signals for both data transmission and environmental perception.
- Contactless Healthcare and Eldercare: Developing non-invasive, wireless technologies for seamless health monitoring and eldercare, ensuring comfort and privacy.
- Battery-free Internet of Things (IoT): Leading the development of sustainable, battery-free IoT devices, enhancing eco-friendliness and ease of use.
- Radio-Visual Joint Learning and Sensing: Combining radio frequency and visual data to create advanced sensing systems that boost accuracy and decision-making capabilities.
WORK EXPERIENCE
Research Fellow supervised by Prof. Andrew Zhang
- Researching & Teaching
- Master/PhD student supervision
Lecturer at College of Information and Engineering
- Researching & Teaching
- Master student supervision
Research Associate supervised by Prof. Min Xu
- Developed an elderly healthcare system using commercial off-the-shelf millimeter-wave devices
- Led the development of key functionalities, including moving object tracking, vital signs estimation, fall detection, stationary object localization, and people counting
- Designed low-computational cutting-edge algorithms to enhance the real-time performance of the system
- Provided valuable mentorship and guidance to Ph.D. students
Research Engineer and Research Assistant supervised by Prof. Andrew Zhang
- Designed a novel device-free WiFi tracking scheme
- Implemented a real-time tracking demonstration system (Demo video available at: https://youtu.be/oIPGrRmY-uc)
- Published the research outcome in an A* top journal
EDUCATION
School of Electrical and Data Engineering
PhD in Engineering supervised by Prof. Min Xu
School of Internet of Things
PhD in Information Network supervised by Prof. Guoliang Chen
School of Computer Science
MS in Computer Software and Theory supervised by Prof. Ning Ye
PUBLICATIONS
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[] Yifeng Jiang, Zhongqin Wang and Haodong Chang. Head Pose Estimation via mmWave Radar. In Proc. of IEEE GLOBECOM, 2024, To Appear. |
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[] Zhongqin Wang, J. Andrew Zhang, Min Xu and Y. Jay Guo. Single-Target Real-Time Passive WiFi Tracking, IEEE Transactions on Mobile Computing, vol.22, no. 6, pp. 3724-3742, 2023. (CORE A*, JCR Q1, IF: 6.075) [Paper] [Demo] |
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[] Kuangda Chen, J. Andrew Zhang, Zhongqin Wang and Y. Jay Guo. Development of an Uplink Sensing Demonstrator for Perceptive Mobile Networks. In Proc. of IEEE ISCIT, pp. 191-196, 2023. [Paper] |
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[] Yingqi Wang, Zhongqin Wang, J. Andrew Zhang, Haimin Zhang, Min Xu. Vital Sign Monitoring in Dynamic Environment via mmWave Radar and Camera Fusion, IEEE Transactions on Mobile Computing, pp. 1-17, 2023, doi:10.1109/ TMC.2023.3288850. [Paper] |
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[] Zhongqin Wang, J. Andrew Zhang, Fu Xiao, Min Xu. Accurate AoA Estimation for RFID Tag Array with Mutual Coupling, IEEE Internet of Things Journal , vol. 9, no. 15, pp. 12954-12972, 2022. (JCR Q1, IF: 10.238) [Paper] |
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[] Zhongqin Wang, Min Xu, Ning Ye, Ruchuan Wang, Haiping Huang and Fu Xiao. Computer Vision-assisted 3D Object Localization via COTS RFID Devices and a Monocular Camera, IEEE Transactions on Mobile Computing, vol. 20, no. 3, pp. 893 - 908, 2021. (CORE A*, JCR Q1, IF: 6.075) [Paper] |
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[] Zhongqin Wang, Min Xu, Fu Xiao. Recognizing 3D Orientation of a Two-RFID-Tag Labeled Object in Multipath Environments Using Deep Transfer Learning. In Proc. of IEEE ICDCS, pp. 652-662, 2021. (CORE A, 97/489) [Paper] |
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[] Zhongqin Wang, Min Xu, Ning Ye, Ruchuan Wang, Haiping Huang and Fu Xiao. RF-Mirror: Mitigating Mutual Coupling Interference in Two-Tag Array Labeled RFID Systems. In Proc. of IEEE SECON, pp. 1-9, 2020. (CORE B, 36/129) [Paper] |
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[] Zhongqin Wang, Min Xu, Ning Ye, Ruchuan Wang and Haiping Huang. RF-Focus: Computer Vision-assisted Region-of-interest RFID Tag Recognition and Localization in Multipath-prevalent Environments. Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies, vol.3, no. 1, pp. 29, 2019. (UbiComp, CORE A*) [Paper] |
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[] Zhongqin Wang, Min Xu, Ning Ye, Ruchuan Wang and Haiping Huang. RF-MVO: Simultaneous 3D Object Localization and Camera Trajectory Recovery Using RFID Devices and a 2D Monocular Camera. In Proc. of IEEE ICDCS, pp. 534-544, 2018. (CORE A, 78/378) [Paper] |
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[] Zhongqin Wang, Fu Xiao, Ning Ye, Ruchuan Wang and Panlong Yang. A See-Through-wall System for Device-free Human Motion Sensing Based on Battery-free RFID, ACM Transactions on Embedded Computing Systems, vol. 17, no. 1, pp. 1-21, 2017. (CORE B, JCR Q3, IF: 1.886) [Paper] |
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[] Fu Xiao, Zhongqin Wang, Ning Ye, Ruchuan Wang and Xiang-Yang Li. One More Tag Enables Fine-Grained RFID Localization and Tracking, IEEE/ACM Transactions on Networking, vol. 26, no. 1, pp. 161-174, 2017. (CORE A*, JCR Q1, IF: 3.796) [Paper] |
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[] Zhongqin Wang, Ning Ye, Reza Malekiand, Fu Xiao and Ruchuan Wang. TrackT: Accurate Tracking of RFID Tags with mm-level Accuracy Using First-order Taylor Series Approximation, Ad Hoc Networks, vol. 53, pp. 132-144, 2016. (JCR Q1, IF: 4.816)[Paper] [Demo] |
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[] Zhongqin Wang, Ning Ye, Reza Malekian, Ruchuan Wang and Peng Li. TMicroscope: Behavior Perception Based on the Slightest RFID Tag Motion. Elektronika ir Elektrotechnika, vol. 22, no. 2, pp.114-122, 2016. (JCR Q3, IF: 1.059) [Paper] [Demo] |
RESEARCH DEMOs
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[mmWave Radar] Elderly Health Monitoring
Our proposed mmWave radar technology, specifically
designed for elderly health monitoring, features a multi-target, contactless sensing algorithm.
This advanced solution simultaneously performs high-precision, real-time tasks such as people
counting, dynamic and static environment sensing, movement tracking, vital signs monitoring, and
fall detection, ensuring comprehensive and simultaneous monitoring for optimal senior care.
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[mmWave Radar] Driver Head Pose Estimation for Enhanced Safety
Our mmWave radar-based head pose estimation system can monitor the driver's head position
within an intelligent vehicle cabin. Unaffected by lighting conditions, this system integrates
with the car's onboard systems to trigger specific safety measures, such as tightening the
seatbelt and reducing speed, thereby enhancing driver safety.
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[WiFi] Real-Time Passive WiFi Tracking
Our WiFi-based tracking system integrates communication and sensing
capabilities to provide real-time indoor human detection and monitoring applications. This innovative
technology enables seamless, accurate tracking and situational awareness within indoor environments,
offering significant improvements in security, automation, and smart home solutions.
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[Passive RFID] Through-wall Human Motion Detection
Our through-wall human motion detection system utilizes passive RFID signals to accurately
monitor movement through obstacles. This cutting-edge technology enables non-invasive, real-time
detection of human activity, offering enhanced security and monitoring capabilities in
various applications, such as building security, healthcare, and smart home environments.
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[Passive RFID] High-Sensitivity Security System
Our system utilizes RFID technology to detect subtle movements of objects, making it
perfect for security and museum applications. This solution provides precise, real-time
monitoring to ensure the safety and preservation of valuable items, offering enhanced protection
and peace of mind.
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[Passive RFID] Object Localization and Monitoring
Our innovative system leverages battery-free RFID signals for precise location tracking. This
technology allows for accurate, non-intrusive monitoring of object
positioning, making it ideal for applications in security, asset management, and
smart home environments.
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RESEARCH PROJECTS
- Zhongqin Wang, Multi-objective Vital Signs Monitoring via Millimeter Wave Radar, R&D Program of Beijing Municipal Education Commission China, Project No. KM202310028005, RMB 150,000 (approx. AUD 31,000), 2023-2024.
- Zhongqin Wang, Research on Object Position and Orientation Estimation based on Fusion of RFID and Millimeter Wave Radar, National Natural Science Foundation, China, Project No. 62302320, RMB 300,000 (approx. AUD 62,000), 2023-2024.
TEACHING
- Tutor, Wireless Communications 32118, University of Technology Sydney, 2024
- Lecturer, Computer Organization for Sophomore Students, Capital Normal University, 2023
- Lecturer, Sensor Network for First-year Graduate Students, Capital Normal University, 2023
PROFESSIONAL SERVICES
- Reviewer, IEEE Global Communications Conference, 2024
- TPC Member, Workshop on Integrated Sensing and Communication at IEEE ICC, 2023
- TPC Member, Workshop on Integrated Sensing and Communication at IEEE ICC, 2023
- Guest Editor, Special Issue "Precise Indoor Positioning and Navigation" of Applied Sciences, 2022
- Reviewer, IEEE Journal of Selected Topics in Signal Processing, 2021
- Reviewer, IJCAI-PRICAI, 2020
- Reviewer, IEEE Access
- Reviewer, Scientific Reports
- Reviewer, IET Communications
- Reviewer, Measurements
AWARDS & HONORS
- Winner, The "Chunhui Cup" Chinese Oversea Students Innovation and Entrepreneurship Competition, 2022
- UTS President's Scholarship, 2017
- National Scholarship for Doctoral Students, 2017
- First Prize, the 2nd National College "3S" (Smart, Service, and System) Competition on Internet of Things Technology and Applications, 2016
- National Scholarship for Graduate Students, 2013
- National Scholarship for Undergraduate Students, 2009
PROGRAMMING SKILLS
- MATLAB
- Python
- C#
- C/C++
- Linux