Qin Chen 陈钦

Qin Chen 陈钦

Ph.D of Information and Communication Engineering

University of Electronic Science and Technology of China (UESTC)

Biography

Hi, my name is Chen Qin, currently pursuing a doctor degree at the University of Electronic Science and Technology of China. My research encompasses millimeter-wave radar gesture recognition, radar system design, and edge computing. I am passionate about exploring the application of radar technology in gesture recognition and dedicated to designing efficient radar systems. I have a keen interest in high-speed RF hardware design and electromagnetic simulation based on bounce-ray techniques. I also maintain a strong enthusiasm for wearable smart devices, specifically focusing on the lightweight deployment of intelligent models (TinyML) on resource-constrained hardware.

Interests
  • Internet of Things 🌐
  • Mobile Computing 📱
  • Artificial Intelligence for Sensing 🤖
  • Radar signal processing 📡
  • Sparse array signal processing 📊
  • Design of radar system ⚡
  • Human-Computer Interaction 🖐️
Education

  • PhD in Information and Communication Engineering, 2022

    University of Electronic Science and Technology of China (UESTC)

  • MEng in Information and Communication Engineering, 2020

    University of Electronic Science and technology of China (UESTC)

  • BSc in Electronic Information Engineering, 2016

    University of Electronic Science and technology of China (UESTC)

Projects

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All MMHTSR RadarStream mmscribe Other
MMEngine

MMEngine

A next-generation multimodal data acquisition engine with blueprint node design, featuring real-time visualization, synchronized annotation, and deep learning inference capabilities.

Code Slides Follow
RadarEngine

RadarEngine

A C/C++ radar data acquisition and visualization software built with ImGui framework, simplifying radar operation with integrated firmware update, data collection, signal processing, and real-time visualization.

Code Slides Follow
mmScribe

mmScribe

An innovative Aerial Handwriting system that enables contactless human-computer interaction through millimeter-wave radar technology.

Code Slides Follow
HCI Gesture Control

HCI Gesture Control

A mid-to-long range gesture control system for smart TVs using mmWave radar, enabling seamless device-free interaction through HID simulation.

Code Slides Follow
MMHTSR

MMHTSR

In-air Handwriting Trajectory Sensing and Reconstruction based on mmWave Radar.

PDF Code Slides Follow
RadarSensing

RadarSensing

A comprehensive radar sensing upper computer software integrating real-time data acquisition, time-frequency signal visualization, vital signs monitoring, and motion recognition.

Code Slides Follow
RadarStream

RadarStream

A real-time raw data acquisition, processing, and visualization system for TI MIMO mmWave radar series with multi-threaded architecture and comprehensive feature extraction.

Code Slides Follow
mmWave Radar Near-Field Imaging System

mmWave Radar Near-Field Imaging System

A DIY 2D scanning platform for millimeter-wave radar near-field imaging using GRBL-controlled linear rails and integrated data acquisition and imaging algorithms.

Code Slides Follow
Radar-Camera Fusion

Radar-Camera Fusion

An early-stage master’s research project exploring late fusion strategy for multi-sensor target detection and tracking by integrating mmWave radar point clouds with camera-based object detection.

Code Slides Follow

Gallery

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Recent Publications

Quickly discover relevant content by filtering publications.
**Chen Q**, Chen Y, Tian Y, Cao Z (2025). Domain-Generalized mmWave Gesture Recognition via Multi-View Learning. preprint.

Code Dataset Poster Slides Video Source Document Custom Link

**Chen Q**, Tian Y, Chen Y, Cao Z (2025). mmScribe: Streaming End-to-End Aerial Handwriting Text Translation via mmWave Radar. preprint.

Code Dataset Poster Slides Video Source Document Custom Link

**Chen Q**, Cui Z, Tian Y, Cao Z (2024). Joint position estimation for hand motion using MIMO FMCW mmWave radar. IEEE IoT J.

PDF Cite Slides

**Chen Q**, Cui Z, Zhou Z, Tian Y, Cao Z (2023). MMHTSR: In-air handwriting trajectory sensing and reconstruction based on mmWave radar. IEEE IoT J.

PDF Cite Code Slides DOI

Contact

  • qinchen_uestc@163.com
  • No. 2006, Xiyuan Ave, West Hi-Tech Zone, Chengdu, China, 611731
  • Find me online or in person at the Research Building B area.
  • Every day 10:00 to 23:00

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