Embedded Systems • Wireless Sensing • Applied ML

Thai Ha Dang

PhD student in Electrical Engineering focused on wearable embedded devices, wireless sensing systems, RF energy harvesting, and machine learning for signal processing.

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Location Denton, Texas, USA
TH

Research Focus

  • Wearable embedded systems
  • Underwater monitoring systems
  • RF energy harvesting
  • BLE and low-power wireless devices
  • Signal processing and applied ML

About

Summary

I am a graduate researcher with a strong background in wearable embedded devices for both human and animal models. My work combines hardware prototyping, firmware development, wireless sensing, and machine learning to build practical monitoring systems. I have hands-on experience designing and debugging sensing platforms, multi-layer PCBs, and RF energy harvesting systems, with a growing focus on intelligent sensing for agriculture and underwater environments.

Education

Academic Background

Sep 2023 - Present

University of North Texas

PhD in Electrical Engineering

Sep 2021 - Aug 2023

Pukyong National University, Korea

M.S. in Electrical Computer Engineering • GPA: 4.12/4.5

Sep 2016 - Dec 2020

Hanoi University of Science and Technology

Engineer in Electrical Engineering • Talent Program of Automatic Control • GPA: 3.23/4.0 (Top 15%)

Skills

Technical Strengths

Programming

C/C++, MATLAB, Python

Embedded & Tools

STM32CubeIDE, Arm Keil MDK, Altium Designer, Git

Protocols & Platforms

I2C, SPI, UART, JTAG, BLE, STM32, nRF52, ARM Cortex-M4

Lab Equipment

Oscilloscope, impedance analyser, logic analyser, soldering station

Experience

Research & Industry

Research Assistant • Embedded Sensing & Processing Systems Lab

University of North Texas • Sep 2023 - Present

Advisor: Prof. Xinrong Li

  • Designing underwater monitoring systems.
  • Supporting teaching activities in the Department of Electrical Engineering.

Graduate Student Researcher • AIOT Lab

Pukyong National University • Sep 2021 - Aug 2023

Advisor: Prof. Wan-Young Chung

  • Developed a computing system for cow behavior classification using sensor data and machine learning.
  • Built full prototypes including 4-layer PCB design, firmware, and mechanical design.
  • Developed wearable, low-power, multi-channel embedded devices for monitoring applications.

Engineer, AI Group • Samsung Display Vietnam

Jan 2021 - Aug 2021
  • Trained, evaluated, and deployed computer vision models.
  • Worked on neural-network-based defect detection for display screens.

Projects

Selected Work

CPS: Medium

Integrated sensors, controls, and ecotoxicology with decoupled aquaponics using brackish groundwater and desalination concentrate for sustainable food production.

USDA + NSF

Cow Behavior Monitoring

Developed a wearable sensing prototype with RF energy harvesting and deep learning models for classifying cow behaviors. Evaluated energy harvesting capacity and real-world device operation experimentally.

Smart Agriculture

Food Quality Monitoring

Built a battery-free food monitoring system powered by 915 MHz RF energy harvesting to estimate food freshness using pH, TVOC concentration, and package pressure data.

Battery-Free Sensing

Publications

Research Output

  • Thai-Ha Dang, L. Nkenyereye, V.-T. Tran, and W.-Y. Chung, “Self-Powered Cattle Behavior Monitoring System Using 915 MHz Radio Frequency Energy Harvesting,” IEEE Access.
  • Thai-Ha Dang, Jaehee Park, Viet-Thang Tran, and W.-Y. Chung, “VAE-LSTM Data Augmentation for Cattle Behavior Classification Using a Wearable Inertial Sensor,” IEEE Sensor Letters.
  • Ngoc-Hai Dang, Viet-Thang Tran, Thai-Ha Dang, and Wan-Young Chung, “Radio-Frequency Energy Harvesting-based Self-Powered Dairy Cow Behavior Classification System,” IEEE Sensors Journal.
  • Thai-Ha Dang, Ngoc-Hai Dang, Viet-Thang Tran, and Wan-Young Chung, “A LoRaWAN-Based Smart Sensor Tag for Cow Behavior Monitoring,” IEEE Sensors Conference 2022.
  • Thai-Ha Dang, Ngoc-Hai Dang, Viet-Thang Tran, and Wan-Young Chung, “B2EH: Batteryless BLE Sensor Network Using RF Energy Harvesting,” IEEE Applied Sensing Conference 2023.
  • Thai-Ha Dang, Xinrong Li, “Shrimp Larvae Counting in Dense Environments Using Size-Adaptive Density Map Estimation and Multi-scale Feature Network,” IEEE Transactions on AgriFood Electronics (accepted).

Recognition

Awards & Professional Service

Honors & Awards

  • Best Paper Award, KICSP 2021
  • Brain Korean 21 Scholarship (2021 - 2023)
  • Research assistantship at Pukyong National University
  • Research assistantship at University of North Texas

Peer Review Service

Reviewed 41 times for 9 journals, including:

  • Alexandria Engineering Journal
  • Biomedical Signal Processing and Control
  • Computers and Electronics in Agriculture
  • Journal of Agriculture and Food Research
  • Smart Agricultural Technology

Contact

Let’s Connect

Email: [email protected]

Phone: (+1) 773-461-7502

GitHub: hadt222

LinkedIn: https://www.linkedin.com/in/thaiha98/