Assist. Prof. Dr. Zhushanying Zhang, South-Central Minzu University, China
Dr. Zhushanying Zhang holds a Ph.D. in Mechanical and Electronic Engineering from the School of Mechanical Science and Engineering, Huazhong University of Science and Technology. His research focuses on infrared spectroscopy detection, machine learning, optoelectronic detection, and fiber optic sensing. Dr. Zhang has led multiple National Natural Science Foundation of China-funded projects and received special funding for basic scientific research. He has published over ten academic papers and holds three invention patents. His work includes advancing Fourier infrared spectroscopy for noninvasive diabetes diagnosis through blood, urine, and saliva samples. 🔬📑💡
Publication Profile
Scopus
Academic and Professional Background
Assist. Prof. Dr. Zhushanying Zhang graduated with a Ph.D. in Mechanical and Electronic Engineering from the School of Mechanical Science and Engineering at Huazhong University of Science and Technology. His research focuses on infrared spectroscopy detection, machine learning, optoelectronic detection, and fiber optic sensing. Dr. Zhang has led and participated in several research projects funded by the National Natural Science Foundation of China, alongside special funding for basic scientific research from central universities. He has published over ten high-quality academic papers as the first or corresponding author and holds three invention patents. 📚💡📑
Research and Innovations
Assist. Prof. Dr. Zhushanying Zhang has led multiple innovative research projects focused on non-invasive detection technologies. His completed projects include the “Highly Accurate Glucose Detection Using Mid-Infrared Absorption Spectroscopy” (2022-2023, 50,000 Yuan) and “Non-invasive Uric Acid Detection by Near-Infrared Spectroscopy” (2018-2020, 40,000 Yuan), both funded by the Fundamental Research Funds for Central Universities. He also presided over the “Non-invasive Detector for Human Weak Components” (2021-2023, 100,000 Yuan) and “Human Saliva Infrared Spectroscopy Detection” (2022-2023, 500,000 Yuan). His work in Fourier infrared spectroscopy offers promising advancements for diabetes diagnosis using blood, urine, and saliva samples. 🧬📊
Research Areas
Assist. Prof. Dr. Zhushanying Zhang’s research spans across multiple cutting-edge fields. His expertise in infrared spectroscopy and fiber optic sensing focuses on non-invasive medical diagnostics, particularly for glucose and uric acid detection. Utilizing machine learning techniques, he enhances the accuracy and efficiency of sensor data analysis. His work in medical sensing aims to revolutionize healthcare by developing innovative detection technologies. Additionally, Dr. Zhang applies chemometrics to optimize data interpretation, advancing the potential of these technologies for real-world applications, especially in diagnostics and healthcare monitoring. 🔍💡📈
Publication Top Notes
- “Advances in Fourier infrared spectroscopy for noninvasive diagnosis of diabetes mellitus: Analysis and prospects for application based on blood, urine, and saliva samples” (2024) 📄
- “Precise measurement of human heart rate based on multi-channel radar data fusion” (2024) 📄
- “A comprehensively improved local binary pattern framework for texture classification” (2024) 📄
- “Identifying the Role of Disulfidptosis in Endometrial Cancer via Machine Learning Methods” (2023) 📄 | Cited by 1
- “Quantitative Analysis of Hemoglobin Based on SiPLS-BP Model” (2023) 📄 | Cited by 2
- “Texture classification combining improved local binary pattern and threshold segmentation” (2023) 📄 | Cited by 12
- “Mid-infrared spectroscopy with an effective variable selection method based on MPA for glucose detection” (2023) 📄 | Cited by 5
- “Influencing Factors of Mid-Infrared Spectrum Blood Glucose Detection” (2023) 📄 | Cited by 2
- “Quantitative Analysis of Hemoglobin Based on SiPLS-SPA Wavelength Optimization” (2023) 📄 | Cited by 3
- “Thermal performance of LED filament in flip-chip packaging manufactured for different correlated color temperature” (2021) 📄 | Cited by 1