Shougui Zhang | Computational mathematics | Best Researcher Award

Published on 11/11/2025 by Global Scholar Awards

Prof. Dr. Shougui Zhang | Computational mathematics | Best Researcher Award

Teacher| Chongqing Normal Univercity | China

Dr. Xin Li is an accomplished scholar and educator specializing in clinical medicine and sports health sciences, currently serving as an Associate Professor at Tianjin Normal University since 2006. She obtained her Doctor of Medicine (MD) in Clinical Medicine from Tianjin Medical University in July 2006. Over nearly two decades of academic and research experience, Dr. Li has established herself as a leading expert at the intersection of clinical medicine, exercise science, and health management. Her teaching portfolio encompasses a range of courses in sports health, exercise rehabilitation, and health management, with a focus on integrating clinical case studies into theoretical instruction to enhance students’ practical competencies and professional insight. Dr. Li’s research primarily addresses exercise interventions for chronic diseases, sports injury prevention, and rehabilitation science, contributing to the growing evidence base linking physical activity with disease prevention and functional recovery. She has led and participated in numerous provincial and municipal research projects, achieving notable outcomes that have advanced the application of medical principles in sports health practice. To date, Dr. Li has published over ten academic papers in peer-reviewed core journals and international conferences, several of which have been widely cited and recognized within the academic community for their methodological rigor and clinical relevance. Her collaborative approach bridges disciplines such as physiology, public health, and kinesiology, fostering innovation and interdisciplinary integration in sports medicine research. Beyond academia, Dr. Li’s work holds significant societal impact, promoting the scientific development of exercise-based health strategies for chronic disease management and population well-being. Combining solid clinical expertise, pedagogical excellence, and a strong research record, Dr. Xin Li continues to contribute meaningfully to the advancement of sports health education and evidence-based medical practice in China and beyond.

Profile: Scopus | ORCID

Featured Publications

Zhang, S. (2025). A self-adaptive alternating direction multiplier method for variational inequality in two domains. Applied Mathematics and Mechanics.

Zhang, S., & Coauthors. (2025). Analysis of a Crank–Nicolson fast element-free Galerkin method for the nonlinear complex Ginzburg–Landau equation. Journal of Computational and Applied Mathematics.

Zhang, S. (2024). Self-adaptive alternating direction method of multiplier for a fourth order variational inequality. Journal of Inequalities and Applications.

Professor Shougui Zhang’s research advances the development of efficient computational methods for complex variational inequalities and partial differential equations, strengthening the mathematical foundation for modern engineering, physics, and optimization problems. His work enhances scientific computing capabilities, supporting innovation in technology, modeling, and data-driven decision-making across academic and industrial domains worldwide.

To Dang | Coastal Engineering | Best Researcher Award

Published on 18/09/202518/09/2025 by Global Scholar Awards

Dr. To Dang | Coastal Engineering | Best Researcher Award

Lecturer | California State University, Dominguez Hills | United States

Dr. To Dang is a physicist and coastal engineer with extensive expertise in fluid mechanics, wave dynamics, sediment transport, and coastal morphodynamics, combining strong theoretical foundations with applied research in environmental and engineering contexts. He earned his B.S. in Physics from the University of Ho Chi Minh City in 1984, an M.Eng. in Coastal Engineering from the Asian Institute of Technology in 1993, and a Ph.D. in Coastal and Environmental Engineering from the University of New South Wales, Australia, in 2007. Over the past four decades, Dr. Dang has held academic and professional positions including Assistant Lecturer, Lecturer, and Senior Lecturer at the University of Science, Ho Chi Minh City; Senior Coastal Scientist at Environmental Science Associates, San Francisco; and currently Lecturer in the Department of Physics at California State University, Dominguez Hills. His research interests lie at the intersection of physics and engineering, focusing on nonlinear shallow water equations, sediment transport processes, hydrodynamic modeling, and the application of computational methods and AI-informed models to both environmental systems and education. He is skilled in advanced mathematical modeling, experimental design, and computer-based simulation tools that address real-world challenges in coastal engineering and physics education. Dr. Dang has published in internationally recognized journals such as Journal of Fluid Mechanics and Coastal Engineering, contributed to IEEE and Scopus-indexed conferences, and supervised more than 60 theses across physics and engineering disciplines. His honors include multiple competitive scholarships, such as the New Zealand Foreign Aid Master Scholarship, AusAID Ph.D. Scholarship, and recognition as the “Most Favorite Lecturer” at Saigon Technology University. Through teaching, mentoring, and leadership roles—including serving as Chapter Chair of the Vietnam Physics Society—he has significantly contributed to advancing both research and STEM education. His dedication, international collaborations, and scholarly outputs make him a strong candidate for recognition. Citations by 68 documents; 2 documents; h-index: 2.

Profiles: Scopus | ORCID

Featured Publication

Dang, T. (1997). Flood and typhoon disasters in Viet Nam in the half century since 1950. Natural Hazards, 15(1), 71–87. Citations: 52

Mohammad Shifat-E-Rabbi | Mathematical Modeling | Best Researcher Award

Published on 25/02/202525/02/2025 by Global Scholar Awards

Dr. Mohammad Shifat-E-Rabbi | Mathematical Modeling | Best Researcher Award

Assistant Professor at North South University, Bangladesh

Dr. Mohammad Shifat-E-Rabbi is an Assistant Professor in the Department of Electrical and Computer Engineering at North South University, Bangladesh. He earned his Ph.D. in Biomedical Engineering from the University of Virginia, where his dissertation, “Transport Generative Models in Pattern Analysis and Recognition,” focused on developing mathematical and computational frameworks for artificial intelligence and machine learning. Dr. Shifat-E-Rabbi’s research interests include applied mathematics, machine learning, image informatics, computational biology, and pattern recognition. He has contributed to various publications, such as “End-to-End Signal Classification in Signed Cumulative Distribution Transform Space” in IEEE Transactions on Pattern Analysis and Machine Intelligence. At North South University, he teaches courses in Artificial Intelligence, Machine Learning, and programming languages. His academic journey began with a B.Sc. in Electrical and Electronic Engineering from the Bangladesh University of Engineering and Technology.

Professional Profile

Google Scholar
Scopus Profile
ORCID Profile

Education

Dr. Mohammad Shifat-E-Rabbi’s educational journey began at Rangpur Zilla School and Rangpur Cadet College in Bangladesh. He earned his B.Sc. in Electrical and Electronic Engineering from the Bangladesh University of Engineering and Technology (BUET) in 2015. He then pursued his Ph.D. in Biomedical Engineering at the University of Virginia (UVa), USA, focusing on Pattern Analysis and Recognition within the Imaging and Data Science Laboratory. His dissertation, titled “Transport Generative Models in Pattern Analysis and Recognition,” centered on developing mathematical and computational frameworks for artificial intelligence and machine learning. During his doctoral studies, Dr. Shifat-E-Rabbi served as a research assistant under the supervision of Prof. Gustavo Rohde.

Professional Experience

Dr. Mohammad Shifat-E-Rabbi is an Assistant Professor in the Department of Electrical and Computer Engineering at North South University, Bangladesh. He earned his Ph.D. in Biomedical Engineering from the University of Virginia, USA, where he specialized in Pattern Analysis and Recognition within the Imaging and Data Science Laboratory. During his doctoral studies, Dr. Shifat-E-Rabbi served as a research assistant under the supervision of Prof. Gustavo Rohde. Prior to his Ph.D., he completed his B.Sc. in Electrical and Electronic Engineering at the Bangladesh University of Engineering and Technology (BUET) in 2015. At BUET, he was involved in the Digital Signal Processing research lab. Dr. Shifat-E-Rabbi’s research interests encompass applied mathematics, machine learning, image informatics, computational biology, and pattern recognition. In his current role, he teaches courses in Artificial Intelligence, Machine Learning, and programming languages. His academic journey began at Rangpur Zilla School and Rangpur Cadet College in Bangladesh.

Research Interest

Dr. Mohammad Shifat-E-Rabbi’s research interests encompass applied mathematics, machine learning, image informatics, computational biology, and pattern recognition. He has contributed to the development of the Radon Signed Cumulative Distribution Transform (R-CDT) and its applications in classifying signed images. Additionally, he has worked on predictive modeling of hematoma expansion in intracerebral hemorrhage patients and the real-time intelligent classification of COVID-19 and thrombosis through massive image-based analysis of platelet aggregates. Dr. Shifat-E-Rabbi has also explored transport-based morphometry for analyzing nuclear structures in digital pathology images across various cancers. His work aims to bridge theoretical advancements with practical applications, enhancing the understanding and analysis of complex biological and medical data.

Award and Honor

Dr. Mohammad Shifat-E-Rabbi has been recognized for his significant contributions to the fields of artificial intelligence and machine learning. His collaborative research on “End-to-End Signal Classification in Signed Cumulative Distribution Transform Space” was published in the prestigious IEEE Transactions on Pattern Analysis and Machine Intelligence. This work, conducted alongside colleagues from the University of Virginia, received support from esteemed institutions such as the National Institutes of Health and the Office of Naval Research, underscoring its impact and importance.

Research Skill

Dr. Mohammad Shifat-E-Rabbi possesses a robust set of research skills that bridge applied mathematics, machine learning, and computational biology. His expertise includes developing mathematical models and computational frameworks, notably in pattern recognition and image informatics. Dr. Shifat-E-Rabbi has contributed to the advancement of the Radon Cumulative Distribution Transform (R-CDT), enhancing image classification techniques. His collaborative work on “End-to-End Signal Classification in Signed Cumulative Distribution Transform Space” exemplifies his ability to integrate theoretical concepts with practical applications, leading to more efficient signal classification methods. His research portfolio demonstrates proficiency in handling complex datasets, developing innovative algorithms, and applying interdisciplinary approaches to solve real-world problems. Dr. Shifat-E-Rabbi’s commitment to advancing artificial intelligence and machine learning is evident through his scholarly publications and ongoing projects.

Conclusion

If the researcher has made significant contributions through innovation, publications, and demonstrated impact, they would be a strong candidate for the Best Researcher Award. However, if the research is still in its early stages or lacks broader validation, additional work on practical applications, benchmarking, and interdisciplinary collaborations could further strengthen their case.

Publications Top Noted

Massive image-based single-cell profiling reveals high levels of circulating platelet aggregates in patients with COVID-19
- Authors: M. Nishikawa, H. Kanno, Y. Zhou, T.H. Xiao, T. Suzuki, Y. Ibayashi, J. Harmon, M. Shifat-E-Rabbi, et al.
- Published in: Nature Communications
- Year: 2021
- Citations: 71
Enabling early detection of osteoarthritis from presymptomatic cartilage texture maps via transport-based learning
- Authors: S. Kundu, B.G. Ashinsky, M. Bouhrara, E.B. Dam, S. Demehri, M. Shifat-E-Rabbi, et al.
- Published in: Proceedings of the National Academy of Sciences
- Year: 2020
- Citations: 57
Cell image classification: a comparative overview
- Authors: M. Shifat-E-Rabbi, X. Yin, C.E. Fitzgerald, G.K. Rohde
- Published in: Cytometry Part A
- Year: 2020
- Citations: 39
Radon cumulative distribution transform subspace modeling for image classification
- Authors: M. Shifat-E-Rabbi, X. Yin, A.H.M. Rubaiyat, S. Li, S. Kolouri, A. Aldroubi, G.K. Rohde
- Published in: Journal of Mathematical Imaging and Vision
- Year: 2021
- Citations: 28
PREHEAT: Precision heart rate monitoring from intense motion artifact corrupted PPG signals using constrained RLS and wavelets
- Authors: M.S. Islam, M. Shifat-E-Rabbi, A.M.A. Dobaie, M.K. Hasan
- Published in: Biomedical Signal Processing and Control
- Year: 2017
- Citations: 26
Blind Deconvolution of Ultrasound Images Using $ℓp\ell_p$ -Norm-Constrained Block-Based Damped Variable Step-Size Multichannel LMS Algorithm
- Authors: M.K. Hasan, M. Shifat-E-Rabbi, S.Y. Lee
- Published in: IEEE Transactions on Ultrasonics, Ferroelectrics, and Frequency Control
- Year: 2016
- Citations: 12
Local sliced Wasserstein feature sets for illumination invariant face recognition
- Authors: Y. Zhuang, S. Li, M. Shifat-E-Rabbi, X. Yin, A.H.M. Rubaiyat, G.K. Rohde
- Published in: Pattern Recognition
- Year: 2025
- Citations: 10
End-to-end signal classification in signed cumulative distribution transform space
- Authors: A.H.M. Rubaiyat, S. Li, X. Yin, M. Shifat-E-Rabbi, Y. Zhuang, G.K. Rohde
- Published in: IEEE Transactions on Pattern Analysis and Machine Intelligence
- Year: 2024
- Citations: 9
Nearest Subspace Search in The Signed Cumulative Distribution Transform Space for 1D Signal Classification
- Authors: A.H.M. Rubaiyat, M. Shifat-E-Rabbi, Y. Zhuang, S. Li, G.K. Rohde
- Published in: IEEE International Conference on Acoustics, Speech and Signal Processing
- Year: 2022
- Citations: 9
Speckle tracking and speckle content based composite strain imaging for solid and fluid filled lesions
- Authors: M. Shifat-E-Rabbi, M.K. Hasan
- Published in: Ultrasonics
- Year: 2017
- Citations: 9