Zhushanying Zhang | Biomedical Engineering | Best Researcher Award

Assist Prof Dr. Zhushanying Zhang | Biomedical Engineering | Best Researcher Award

Assistant Professor at South-Central Minzu University, China

Dr. Zhushanying Zhang is an Assistant Professor at South-Central MinZu University. With a Ph.D. in Mechanical and Electronic Engineering from Huazhong University of Science and Technology, she specializes in infrared spectroscopy detection, machine learning, optoelectronic detection, and fiber optic sensing. Dr. Zhang has led multiple research projects funded by the National Natural Science Foundation of China and has published several high-impact academic papers. Her dedication to advancing technology for non-invasive health diagnostics has contributed significantly to the fields of glucose detection and early tumor screening.

Profile 

Scopus Profile

Strengths for the Award 

  1. Strong Academic Background:
    • Holds a Ph.D. in Mechanical and Electronic Engineering from a prestigious university.
    • Comprehensive understanding of infrared spectroscopy, machine learning, and optoelectronic detection.
  2. Significant Research Contributions:
    • Led multiple funded projects focused on innovative applications of spectroscopy for medical diagnostics, demonstrating leadership and expertise.
    • Authored over ten high-quality papers in reputable journals, indicating a strong publication record and contribution to scientific knowledge.
  3. Patent Portfolio:
    • Holds three patents related to drug infusion devices and detection systems, showcasing innovation and the practical application of research findings.
  4. Diverse Research Focus:
    • Engaged in various fields, including non-invasive medical testing and machine learning applications, demonstrating versatility and relevance to current scientific challenges.
  5. Collaborative Research Efforts:
    • Actively participated in collaborative projects, enhancing the scope and impact of research through interdisciplinary approaches.
  6. Professional Memberships:
    • Membership in relevant professional organizations, such as the Chinese Biomedical Engineering Society, adds credibility and demonstrates commitment to the field.

Education 🎓

Dr. Zhang completed her doctoral studies in Mechanical and Electronic Engineering at Huazhong University of Science and Technology. Her educational background has laid a solid foundation for her interdisciplinary research, blending mechanical sciences, electronic engineering, and biomedical sensing technologies. Through her studies, she has developed expertise in spectroscopic methods and applied machine learning to medical sensing applications.

Experience 💼

With years of experience in the fields of infrared spectroscopy and fiber optic sensing, Dr. Zhang has been deeply involved in both academic and industry-related projects. She has successfully chaired several key research initiatives at South-Central MinZu University, focusing on non-invasive health diagnostics. These projects include the development of methods for glucose detection using mid-infrared spectroscopy, as well as the application of spectroscopy for the analysis of human biological samples like blood and saliva.

Research Interests 🔬

Dr. Zhang’s primary research interests lie in the intersection of infrared spectrum analysis, fiber optic sensing, and medical diagnostics. Her work focuses on non-invasive techniques for monitoring human health, especially for diseases such as diabetes and early cancer detection. By integrating machine learning algorithms with spectroscopic data, Dr. Zhang aims to improve the accuracy of medical sensing devices and develop innovative solutions for healthcare challenges.

Awards 🏆

Dr. Zhang has been recognized for her contributions to science and innovation, especially in the field of medical diagnostics. She has led several research projects funded by prominent institutions like the National Natural Science Foundation of China, and her work has been acknowledged through multiple invention patents. These patents highlight her innovative approach to developing non-invasive diagnostic devices, which are now being considered for commercial and clinical applications.

Publications 📚

  • Yin, J., Wang, G.W., Zhang, Z.S.Y., et al. (2024). Advances in Fourier Infrared Spectroscopy for Noninvasive Diagnosis of Diabetes Mellitus: Analysis and Prospects. Microchemical Journal, 207, 111764. doi:10.1016/j.microc.2024.111764. Cited by: 25 articles.
  • Zhang, Z.S.Y., Zhang, R.J., Gu, H.W., et al. (2024). Research on the Twin Check Abnormal Sample Detection Method of Mid-Infrared Spectroscopy. Spectroscopy and Spectral Analysis, 44(6), 1546-1552. doi:10.3964/j.issn.1000-0593(2024)06-1546-07. Cited by: 10 articles.
  • Yue, Y.S., Zhang, Z.S.Y., et al. (2023). Influencing Factors of Mid-Infrared Spectrum Blood Glucose Detection. Laser & Optoelectronics Progress, 62(24), 300-306. Cited by: 12 articles.
  • Zhang, Z.S.Y., Zhu, S.C., et al. (2023). Quantitative Analysis of Hemoglobin Based on SiPLS-BP Model. Chinese Journal of Lasers, 50(21), 174-180. Cited by: 5 articles.
  • Lv, Y.L., Zhang, Z.S.Y., et al. (2023). Study on the Influence of Four Interferents on Blood Glucose Detection by Mid-Infrared Spectrum. Chemical Reagents, 45(10), 14-20. doi:10.13822/j.cnki.hxsj.2023.0517. Cited by: 8 articles.
  • Zhang, Z.S.Y., et al. (2023). Flexible Stacked Partial Least Squares for Mid-Infrared Spectroscopy Glucose Detection. Spectroscopy, 38, 29-36. Cited by: 6 articles.
  • Sa, J.M., Zhang, Z.S.Y., et al. (2023). Mid-infrared Spectroscopy with an Effective Variable Selection Method for Glucose Detection. Chemometrics and Intelligent Laboratory Systems, 233. doi:10.1016/j.chemolab.2022.104731. Cited by: 14 articles.
  • Zhang, Z.S.Y., et al. (2023). Quantitative Analysis of Hemoglobin Based on SiPLS-SPA Wavelength Optimization. Spectroscopy and Spectral Analysis, 43(1), 50-56. doi:10.3964/j.issn.1000-0593(2023)01-0050-07. Cited by: 4 articles.
  • Zhang, Z.S.Y., et al. (2021). Thermal Performance of LED Filament in Flip-Chip Packaging for Different Correlated Color Temperature. Applied Sciences-Basel, 11(19). doi:10.3390/app11198844. Cited by: 18 articles.
  • Lan, W.W., Zhang, Z.S.Y., et al. (2014). Signal Processing System Based on LabVIEW of Optical Fiber Oxygen Sensor. Instrument Technique and Sensor, (05), 1-3+10. Cited by: 9 articles.

Conclusion ✍️

Dr. Zhushanying Zhang has made significant strides in advancing non-invasive diagnostic technology through her interdisciplinary research in spectroscopy and medical sensing. With numerous high-impact publications, prestigious research grants, and innovative patents, Dr. Zhang continues to shape the future of health diagnostics. Her ongoing research and contributions have the potential to revolutionize how diseases like diabetes are diagnosed and monitored, making her a strong candidate for the Best Researcher Award.

Shiyu Liu | Engineering and Technology | Best Researcher Award

Dr. Shiyu Liu | Engineering and Technology | Best Researcher Award

Lecturer and Postdoctoral researcher at Hebei University, China

Shiyu Liu is a dedicated researcher and lecturer at the College of Quality and Technical Supervision, Hebei University, with extensive experience in spectral detection and battery health monitoring using artificial intelligence methods. He holds a Ph.D. in Engineering from Yanshan University and has furthered his expertise as a visiting PhD student at the University of Huddersfield. Liu has contributed significantly to his field, publishing numerous articles in reputable journals and participating in various national research projects. His strong technical skills in big data analysis and machine learning complement his innovative research endeavors, earning him several prestigious awards and recognition as an excellent graduate. Liu’s commitment to advancing technology and addressing complex issues positions him as a leading figure in his areas of study.

Publication profile

Scopus Profile

Education Background

Shiyu Liu has an extensive educational background in engineering, with a focus on Instrument Science and Technology. He is currently pursuing a Ph.D. at Yanshan University, where he has been enrolled since September 2018, under the supervision of Shutao Wang. His research during this period has primarily centered on spectral detection and analysis using artificial intelligence methods. Liu also gained international experience as a visiting Ph.D. student at the University of Huddersfield from October 2022 to October 2023, where he focused on health monitoring of lithium-ion batteries. This combination of rigorous academic training and hands-on research experience positions him well within his field.

Research Experience

Shiyu Liu has over a decade of research experience, currently serving as a lecturer and postdoctoral researcher at the College of Quality and Technical Supervision at Hebei University since April 2014. He holds a Ph.D. in Engineering from Yanshan University, specializing in Instrument Science and Technology. His research primarily focuses on the application of artificial intelligence in spectral detection and battery health monitoring. Liu’s work includes capacity prediction and health monitoring of lithium-ion batteries, employing data-driven methods and electrochemical impedance spectroscopy. He has also researched spectral detection algorithms based on near-infrared spectroscopy, addressing challenges such as weak absorption intensity and high noise interference. His involvement in various national projects, coupled with an impressive publication record in reputable journals, highlights his significant contributions to advancing technology in his fields of expertise. Additionally, his experience as a visiting PhD student at the University of Huddersfield further broadens his research perspective and collaborative opportunities.

Teaching and Mentoring Experience

Shiyu Liu has accumulated substantial teaching and mentoring experience as a lecturer at the College of Quality and Technical Supervision, Hebei University, since April 2014. In this role, he has effectively delivered course content on Instrument Science and Technology, fostering a deep understanding of complex subjects among his students. Liu is dedicated to creating an engaging learning environment, employing innovative teaching methods to cater to diverse learning styles. Additionally, he has actively mentored undergraduate and graduate students, guiding them in their research projects and fostering their academic development. His commitment to student success is evident in the positive feedback he receives, reflecting his ability to inspire and motivate learners. Liu’s experience in teaching and mentoring has not only enhanced his pedagogical skills but also contributed to the academic growth of his students, preparing them for future challenges in the field.

Work Experience

Shiyu Liu has accumulated extensive work experience since April 2014, serving as a lecturer and postdoctoral researcher at the College of Quality and Technical Supervision at Hebei University. His academic journey includes pursuing a Ph.D. in Instrument Science and Technology at Yanshan University from September 2018 to January 2024, where he focused on spectral detection and analysis using artificial intelligence methods. Additionally, Liu gained valuable international exposure as a visiting PhD student at the University of Huddersfield from October 2022 to October 2023, specializing in battery health monitoring through artificial intelligence. His roles have enabled him to engage in various research projects, contributing to advancements in environmental pollution

Awards, Honours & Certificates

Shiyu Liu has received numerous awards and honors that reflect his academic excellence and research contributions. Notably, he was awarded the CSC Scholarship in July 2022 for his participation as a visiting PhD student. He has also been recognized as an “excellent graduate” of Hebei Province and Yanshan University in 2021, showcasing his outstanding academic performance. Additionally, Liu received a national scholarship for postgraduates in December 2020, along with several accolades in competitions, including a second prize in the third mathematical modeling competition for postgraduates in Hebei and a first prize in the national university students’ electrical math modeling competition organized by the Chinese Society for Electrical Engineering. His commitment to academic and extracurricular excellence is further evidenced by his recognition as a “three good student” at both the university and provincial levels. Overall, these awards and honors underscore Liu’s dedication, talent, and contributions to his field.

Publication Top Notes

  • State of Health Estimation of Lithium-Ion Batteries via Electrochemical Impedance Spectroscopy and Machine Learning
    • Authors: Liu, S., Wang, S., Hu, C., Zhao, X., Gu, F.
    • Year: 2024
    • Citations: 0
  • Series fusion of scatter correction techniques coupled with deep convolution neural network as a promising approach for NIR modeling
    • Authors: Liu, S., Wang, S., Hu, C., Kong, D., Yuan, Y.
    • Year: 2023
    • Citations: 12
  • A MLP-Based Transfer Learning Model Using EIS Health Features for State of Health Estimation of Lithium-Ion Battery
    • Authors: Zhao, X., Wang, Z., Liu, S., Gu, F., Ball, A.
    • Year: 2023
    • Citations: 0
  • Markov Transform Field Coupled with CNN Image Analysis Technology in NIR Detection of Alcohols Diesel
    • Authors: Liu, S., Wang, S., Hu, C., Kong, D.
    • Year: 2023
    • Citations: 0
  • Rapid and accurate determination of diesel multiple properties through NIR data analysis assisted by machine learning
    • Authors: Liu, S., Wang, S., Hu, C., Kong, D., Wang, J.
    • Year: 2022
    • Citations: 11

Conclusion

Shiyu Liu is an exemplary candidate for the Best Researcher Award, with a strong foundation in research, impressive academic credentials, and a significant contribution to his field through publications and projects. His innovative work in health monitoring and spectral analysis, combined with his technical skills and recognition within the academic community, make him a standout researcher. By addressing areas for improvement, particularly in interdisciplinary collaboration and public engagement, Liu can enhance his research impact and continue to be a leading figure in his field.