lecturer at Jiangsu College of Engineering and Technology , China
Fei Huang 👩🔬 is a dynamic researcher and lecturer in textile engineering, specializing in flexible and stretchable strain sensors 🧵🔋. She earned her PhD from Donghua University under the guidance of Prof. Jiyong Hu and Xiong Yan 🎓. Her cutting-edge work on wearable sensor technologies has led to several high-impact journal publications and innovative patents 📄💡. Currently teaching at Jiangsu College of Engineering and Technology 👩🏫, she blends scientific rigor with practical application. Fei is passionate about smart textiles, precision agriculture 🌿, and human-motion tracking 👟. Her skills in research, technology, and collaboration make her a rising star 🌟 in smart material science.
Professional Profile
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Education & Experience
Fei Huang began her academic career at Jiangnan University 🏫, where she earned a B.S. in Textile Science and Engineering 🎓 (2015–2019). She pursued a PhD at Donghua University in Shanghai 🧪, researching flexible and stretchable strain sensors under Professors Jiyong Hu and Xiong Yan (2019–2025) 📘. Following her doctorate, she joined Jiangsu College of Engineering and Technology in Nantong as a lecturer 👩🏫 in March 2025. Her academic journey reflects a strong foundation in textile science 🧵 and a commitment to advancing wearable sensor technology 🤖. Fei has evolved into an experienced researcher and educator in smart materials.
Professional Development
Fei Huang has developed a diverse skill set combining textile engineering 🧵, materials science 🧬, and sensor technology 📊. She is proficient in software like MATLAB, SPSS, ABAQUS, CAD, and Photoshop 💻, supporting her deep technical analysis and design capabilities. Fluent in both Mandarin and English 🌐, she collaborates effectively on global research projects. She demonstrates strength in laboratory techniques, literature review, and data interpretation 🔍. With hobbies including running, hiking, and reading 🏃♀️📚, Fei maintains balance in her academic life. Her commitment to continuous learning and innovation 🔄 positions her as a forward-thinking researcher in wearable technology.
Research Focus
Fei Huang’s research focuses on flexible, stretchable, and wearable strain sensors 🧵🔋. Her innovations target real-time motion monitoring 🦵, gait analysis 🚶♀️, and precision agriculture 🌾 through sensor integration into textiles. She designs yarn-based capacitive and resistive sensors with ultra-low detection limits and high responsiveness ⚙️. Her work explores encapsulation, structural design, and braiding technologies to improve sensor performance and durability 🔄. Fei also investigates graphene-based devices for environmental sensing 🌿. Her contributions lie at the intersection of smart textiles, wearable electronics, and functional materials, aiming to make textile-integrated electronics practical for health, sports, and agricultural use 🤖🌍.
Awards & Honors
Fei Huang has received notable awards for her academic and research achievements 🏆. She earned the National Scholarship (2017–2018) for outstanding performance 🌟 and was honored with First-Class (2015–2016) and Third-Class (2016–2017) Academic Scholarships 📘. In 2022, she received the Graduate Student Innovation Fund and Fundamental Research Funds for the Central Universities at Donghua University 💡—a testament to her innovative sensor work. These honors reflect her dedication to academic excellence and research impact 📖. With her track record of recognition and productivity, Fei stands out as a promising contributor to the future of smart material technologies 🧪.
Publication Top Notes
1. A Wide-linear-range and Low-hysteresis Resistive Strain Sensor Made of Double-threaded Conductive Yarn for Human Movement Detection
Journal: Journal of Materials Science & Technology
Publication Date: February 2024
DOI: 10.1016/j.jmst.2023.06.047
Authors: Fei Huang, Jiyong Hu, Xiong Yan
🔍 Summary:
This study introduces a novel resistive strain sensor composed of double-threaded conductive yarn engineered for wide linear range and minimal hysteresis. The sensor demonstrates high sensitivity and durability, making it ideal for human movement detection applications such as wearable health monitors and motion tracking suits. The work emphasizes material optimization and structural innovation to enhance repeatability and responsiveness, paving the way for smart textile integration in biomechanical systems.
2. High-linearity, Ultralow-detection-limit, and Rapid-response Strain Sensing Yarn for Data Gloves
Journal: Journal of Industrial Textiles
Publication Date: June 2022
DOI: 10.1177/15280837221084369
Authors: Fei Huang, Jiyong Hu, Xiong Yan, Fenye Meng
🔍 Summary:
This paper presents a strain sensing yarn with exceptional linearity, low detection threshold, and fast response time. Designed specifically for data gloves, this sensor enables accurate hand gesture recognition and real-time motion monitoring. The research blends material engineering and textile design to create a sensor with strong durability, making it suitable for immersive human–machine interface technologies, virtual reality, and robotic control applications.
3. Review of Fiber- or Yarn-Based Wearable Resistive Strain Sensors: Structural Design, Fabrication Technologies and Applications
Journal: Textiles
Publication Date: February 2022
DOI: 10.3390/textiles2010005
Authors: Fei Huang, Jiyong Hu, Xiong Yan
🔍 Summary:
This comprehensive review covers recent advancements in fiber- and yarn-based resistive strain sensors for wearable electronics. The authors analyze structural designs, material compositions, and fabrication techniques, along with their applications in health monitoring, sports, and robotics. The review serves as a valuable guide for researchers and engineers developing next-generation smart textiles, offering insight into performance optimization and integration strategies for flexible electronics.
Conclusion
Fei Huang’s originality, impact, and interdisciplinary contributions make her an ideal recipient for awards such as:
Best Researcher Award, AI and Smart Technology Innovation Awards, or Young Scientist Award.
Her commitment to creating intelligent wearable systems that address real-world needs places her at the forefront of next-generation sensor research.