Donglin Zu | Physics and Astronomy | Research Excellence Award

Prof. Donglin Zu | Physics and Astronomy | Research Excellence Award

Peking University | China

Prof. Donglin Zu is a distinguished physicist whose career spans pioneering contributions to electromagnetics, nuclear magnetic resonance (NMR), magnetic resonance imaging (MRI), and, more recently, photon structure theory. His early work involved teaching electromagnetics and developing an independent NMR magnetometer, along with solving key control challenges in high-voltage electrostatic accelerators. His international research experience includes studying RF superconducting cavities at Cornell University, followed by leading a major project on the practical design of niobium cavities. Over two decades, he made significant advances in MRI engineering, contributing to wavelet-based medical image fusion, high-resolution NMR spectral reconstruction, shim coil design, permanent-magnet MRI optimization, and low-noise preamplifier development. He authored influential textbooks on electrodynamics and MRI, widely adopted in advanced training and research. His extensive publication record encompasses innovations in superconducting magnets, ferromagnetic shimming, pulse sequence optimization, image contrast mechanisms, and magnet design methodologies. As a long-term consultant to MRI industries, he helped translate theoretical principles into practical imaging technologies. In recent years, his research has shifted toward foundational physics, producing breakthrough models on single-photon structures, standing-wave photon behavior in constrained spaces, and multi-photon composite systems, marking a new phase of theoretical advancement with impactful emerging publications.

Profile : Orcid

Featured Publications

Zu, D. (2025). Standing wave photon structures in constraint spaces. Photonics.

Zu, D. (2025). Standing wave photon structures in constraint spaces [Preprint].

Zu, D. (2025). Single photon structure model and multi-photon composite monomer. Optics Express.

Zu, D. (2016). Electrodynamics (Rev. ed.). Tsinghua University Press.

Zu, D. (2015). Nuclear magnetic resonance imager. Science Press.

Zu, D., & Gao, J. (2014). Nuclear magnetic resonance imaging. Peking University Press.

Liu, W., Casanova, F., Blümich, B., & Zu, D. (2012). An efficacious target-field approach to design shim coils for Halbach magnet of mobile NMR sensors. Applied Magnetic Resonance.

Zhao, X., Wen, Z., Huang, F., Lu, S., Wang, X., Hu, S., Zu, D., & Zhou, J. (2011). Saturation power dependence of amide proton transfer image contrasts in human brain tumors and strokes at 3 T. Magnetic Resonance in Medicine.

Cao, X., Zu, D., Zhao, X., Fan, Y., & Gao, J. (2011). The design of a low-noise preamplifier for MRI. Science China Technological Sciences.

Tang, X., Zu, D., Wang, T., & Han, B. (2010). An optimizing design method for a compact iron-shielded superconducting magnet for use in MRI. Superconductor Science and Technology.

Tang, X., Li-Ming, H., & Zu, D.-L. (2010). Active ferromagnetic shimming of the permanent magnet for magnetic resonance imaging scanner. Chinese Physics B.

Zhao, X., Chen, M., Zhang, C., Hu, S., & Zu, D. (2010). Experimental evaluation of dual acceptance window weighting function for right coronary MR angiography at 3.0 T. Magnetic Resonance Imaging.

Zu, D., Liming, H., Xueming, C., & Xin, T. (2010). Analysis on background magnetic field to generate eddy current by pulsed gradient of permanent-magnet MRI. Science China Series E.

Noelle Clerkin | Health Professions | Best Researcher Award

Ms. Noelle Clerkin | Health Professions | Best Researcher Award

University of Suffolk | United Kingdom

Author profile

Orcid

Early Academic Pursuits 🎓

Ms. Noelle Clerkin embarked on her academic journey with a foundation in health sciences. She completed her BSc (Hons) in Diagnostic Radiography from the University Campus Suffolk in 2009, following her outstanding performance in secondary education, where she earned several honors. Her academic progression is marked by continuous specialization, including a Postgraduate Certificate in Mammography from University College Dublin (2013), further deepening her expertise in breast imaging and clinical communication.

Professional Endeavors 👩‍⚕️

Ms. Clerkin's professional career is diverse and impactful. She currently serves as the Breast Service Manager at the Belfast & Social Health and Care Trust, where she leads the breast imaging services with a strong focus on service modernization and clinical excellence. Her previous roles include serving as a Deputy Breast Service Manager, Lead Clinical Practice Educator, and Advanced Practitioner at the Belfast Trust. She has also been actively involved in academia, contributing as a Visiting Lecturer at the University of Suffolk and an External Examiner at Kingston University.

Contributions and Research Focus 🔬

With a strong focus on breast cancer screening, Ms. Clerkin has made significant contributions through her research and publications. Her work explores factors influencing diagnostic performance in mammography reporting. She has authored papers on the role of Radiography Advanced Practitioners (RAPs) and their impact on breast cancer screening outcomes. Her research has been featured in leading journals like Radiography and presented at international conferences, such as the European Congress of Radiology and UK Imaging and Oncology Congress, highlighting her commitment to advancing breast cancer diagnostics.

Accolades and Recognition 🏆

Ms. Clerkin’s expertise in radiography has been recognized through her multiple speaking engagements and presentations at prestigious conferences across Europe. Her research has earned her a reputable presence in the field of breast cancer imaging, with several conference presentations on RAP performance in breast cancer screening. This continuous contribution to knowledge underscores her role as a thought leader in the radiography and oncology communities.

Impact and Influence 🌍

As both a healthcare leader and academic, Ms. Clerkin has greatly influenced the fields of breast imaging and clinical education. She has played a pivotal role in shaping breast screening services in the Belfast Trust and has contributed to the education and development of radiographers. Her partnership with educational institutions such as the Nottingham Breast Institute of Education further emphasizes her impact on the future of healthcare professionals in the radiography sector.

Legacy and Future Contributions 🌟

Ms. Noelle Clerkin’s legacy lies in her dual roles as a clinical leader and academic scholar. Her ongoing PhD research in Health and Biological Sciences promises to yield further insights into breast cancer diagnostics, while her leadership in breast screening services ensures she continues to make a direct impact on patient care. Looking ahead, her work will likely shape the evolution of breast imaging services and radiography education for years to come.

 

Publications


📄 An initial exploration of factors that may impact radiographer performance in reporting mammograms
Authors: N. Clerkin, C. Ski, M. Suleiman, Z. Gandomkar, P. Brennan, R. Strudwick
Journal: Radiography
Year: 2024


📄 Identification of factors associated with diagnostic performance variation in reporting of mammograms: a review
Authors: N. Clerkin, C.F. Ski, P.C. Brennan, R. Strudwick
Journal: Radiography
Year: 2023


📄 Radiographers filling the mammography screening gap, but where's the evidence?
Authors: N. Clerkin, C.F. Ski, P.C. Brennan, R. Strudwick
Journal: Radiography
Year: 2023


📄 An initial exploration of factors that may impact radiographer reporting of mammography images
Authors: N. Clerkin, C.F. Ski, P.C. Brennan, R. Strudwick
Journal: Radiography
Year: 2024


 

Harikumar Rajaguru | Engineering | Best Researcher Award

Dr. Harikumar Rajaguru | Engineering | Best Researcher Award

Bannari Amman Institute of Technology | India

Author Profile

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Early Academic Pursuits

Dr. Harikumar Rajaguru began his academic journey in electronics and communication engineering. He completed his Bachelor of Engineering in Electronics and Communication Engineering from Regional Engineering College, Trichy, affiliated with Bharathidasan University, in 1988. He then pursued a Master of Engineering in Applied Electronics at the College of Engineering, Guindy, under Anna University Chennai, graduating in 1990. His passion for biomedical signal processing led him to obtain a Ph.D. in Information and Communication Engineering, with a specialization in Bio Signal Processing, from Thiagarajar College of Engineering, Madurai, under Anna University Chennai in 2009. His Ph.D. thesis focused on the use of soft computing techniques and non-linear models for the performance analysis and classification of epilepsy risk levels from EEG signals.

Professional Endeavors

Dr. Rajaguru's professional career spans over 33 years in academia. He began as a lecturer and senior lecturer at PSNA College of Engineering and Technology, Dindigul, where he served for ten years. He then worked as an Assistant Professor at PSG College of Technology, Coimbatore, for one year. His journey continued at Amrita Institute of Technology, Coimbatore, as a Senior Lecturer and Assistant Professor for over two years. Dr. Rajaguru also spent time as a research scholar at Thiagarajar College of Engineering, Madurai. Since 2006, he has been a professor at Bannari Amman Institute of Technology, Sathyamangalam, where he has contributed significantly to the field of biomedical signal processing and soft computing.

Contributions and Research Focus

Dr. Rajaguru has made substantial contributions to biomedical signal processing, particularly in the classification of epilepsy risk levels from EEG signals. He has been involved in several funded projects, including the development of an ASIC fuzzy processor for diabetic epilepsy risk level classification, wavelet networks for epilepsy risk levels classification from EEG signals, and a non-invasive photo plethysmographic-based glucometer for mass diabetes screening. His research primarily focuses on applying soft computing techniques and developing non-linear models for analyzing and classifying biomedical signals.

Accolades and Recognition

Throughout his career, Dr. Rajaguru has received numerous accolades and recognition for his contributions to engineering and biomedical signal processing. He has published multiple papers in SCI-indexed journals and conferences, showcasing his research findings and innovations. His work has been recognized with patents for various biomedical devices, including an electro gastrogram system for detecting gastric disorders, a sensor for stress measurement using photo plethysmography, and a device for detecting ventricular tachycardia. These patents highlight his innovative approach to solving complex biomedical problems.

Impact and Influence

Dr. Rajaguru's work has significantly impacted biomedical signal processing, particularly in the analysis and classification of epilepsy risk levels and the development of non-invasive diagnostic tools. His research has provided new insights into the use of soft computing and wavelet networks in biomedical applications. His contributions have influenced both academic research and practical applications in the medical field, improving diagnostic techniques and patient outcomes.

Legacy and Future Contributions

Dr. Rajaguru's legacy lies in his dedication to advancing biomedical signal processing through innovative research and teaching. He has guided numerous students in their research projects, fostering the next generation of engineers and researchers. As he continues his work at Bannari Amman Institute of Technology, he is poised to make further contributions to the field, particularly in developing new diagnostic tools and techniques for medical applications. His commitment to research and education ensures that his influence will be felt for years to come, both in academia and the broader field of biomedical engineering.

 

Notable Publications

Wavelet feature extraction and bio-inspired feature selection for the prognosis of lung cancer − A statistical framework analysis 2024

Processing of digital mammogram images using optimized ELM with deep transfer learning for breast cancer diagnosis 2023 (5)

Exploration and Enhancement of Classifiers in the Detection of Lung Cancer from Histopathological Images 2023 (6)

Detection of Diabetes through Microarray Genes with Enhancement of Classifiers Performance 2023 (1)

Evaluation and Exploration of Machine Learning and Convolutional Neural Network Classifiers in Detection of Lung Cancer from Microarray Gene—A Paradigm Shift 2023 (6)