Ander Ernaga Lorea | Leadership Development | Research Excellence Award

Published on by Human Resources Management

Mr. Ander Ernaga Lorea | Leadership Development | Research Excellence Award

Doctor | The University of  Hospital Universitario de Navarra | Spain

Mr. Ander Ernaga Lorea is an accomplished researcher in the field of endocrinology and metabolic disorders, with a focus on thyroid diseases, acromegaly, hypercholesterolemia, and cerebrovascular complications. He has contributed as first author to nine peer-reviewed publications in high-impact indexed journals, addressing topics such as prognostic markers in thyroid carcinoma, glycemic alterations in acute stroke, chronic diarrhea as an early symptom of medullary thyroid carcinoma, and subclinical atherosclerosis in familial hypercholesterolemia. His work has been cited 65 times, reflecting the relevance and impact of his research 9 documents within the scientific community. He has also led the project, a strategic initiative applying genomic medicine to hypercholesterolemia. With an h-index of 5, his research demonstrates a commitment to advancing understanding of endocrine and metabolic pathologies through both clinical observation and translational studies.

                            Citation Metrics ( Scopus )

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Featured Publications

 

 

Mizanur Rahman | HR Technology and Digital Transformation | Research Excellence Award

Published on by Human Resources Management

Dr. Mizanur Rahman | HR Technology and Digital Transformation | Research Excellence Award

Lecturer | The University of  Regent College London | United Kingdom

Dr. Md. Mizanur Rahman’s research focuses on advanced computing, data visualization, distributed systems, and data-driven analytics. His work investigates high performance rendering techniques, scanline-based algorithms, and the visualization of large-scale data sets, contributing to efficient computation and graphical modeling in complex computing environments. Across 11 publications, including international conferences and journals such as, Springer. Dr. Rahman has explored areas spanning geometric modeling, distributed computing architectures, and algorithm optimization for visualization tasks. His studies on cache oblivious algorithms, Java-based systems for large-scale rendering, and data-driven business analytics demonstrate a blend of theoretical rigor and practical application. With four citations and an h-index of 1, his contributions provide foundational insights into computational efficiency, algorithm design, and the integration of data science methods into real-world applications. Dr. Rahman’s work supports advancements in both academic research and applied computing technologies.

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View Google Scholar Profile
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Featured Publications


High-performance rendering on clusters of workstations – S Dalal, F Dévai, MM Rahman

– Geometric Modeling and Imaging–New Trends (GMAI’06), 22-27, 2006


Experimental Evaluation of Graphics Algorithms – B Chalk, S Dalal, F Dévai, MM Rahman

– 2008 3rd International Conference on Geometric Modeling and Imaging, 59-65, 2008


The PCC Model in Online Teaching: A Framework for Effective Practice – MM Rahman

– The 2nd International Conference on Education Research – ICER 2025, 2025


Data-driven business strategies with the power of the K-means algorithm – MM Rahman

– International Journal of Higher Education Management 11 (2), 1-10, 2025

 

Juan Xu | Women in Leadership | Best Researcher Award

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Mrs. Juan xu | Women in Leadership | Best Researcher Award

NCWU at The University of North China University of Water Resources and Electric Power | China

Mrs. Xu Juan is a dedicated Lecturer at the School of Electrical Engineering, North China University of Water Resources and Electric Power, recognized for her strong academic foundation and research excellence in electronic science and energy storage materials. She earned her Ph.D. in Electronic Science and Technology from Huazhong University of Science and Technology , following a solid academic path that included a Bachelor’s degree in Physics from Xinxiang University and postgraduate studies in Electronic Science and Technology at the same institution. Since joining her current university in 2018, she has actively engaged in teaching and research, contributing significantly to the fields of zinc-ion and sodium-ion batteries, supercapacitors, and nanostructured materials. Her research interests focus on cation doping regulation, oxygen vacancy engineering, and advanced energy storage technologies, aiming to enhance electrochemical performance and energy efficiency. Mrs. Xu has published 24 scientific papers, receiving 80 citations with an h-index of 5, showcasing her growing academic influence. Her technical expertise includes materials synthesis, electrochemical analysis, and nanomaterial interface engineering, combining theoretical understanding with experimental innovation. She has also contributed to two Chinese patents and was part of a research team that won the Henan Provincial First-Class Award for Scientific and Technological Progress for advancements in high-power nonlinear optical terahertz radiation sources. Her professional strengths lie in collaborative research, analytical problem-solving, and high-quality scholarly output. Looking ahead, Mrs. Xu aims to expand her research through interdisciplinary collaborations and explore next-generation flexible and sustainable energy storage systems. With her academic excellence, innovative mindset, and strong commitment to scientific advancement, she continues to be a promising scholar contributing meaningfully to the development of modern energy technologies.

Profile:  SCOPUS

Featured Publications

Authors unavailable. Enhancing interfacial electron transfer by gradiently constructing polyaniline electron bridge between MOF and MnOx for high-performance flexible supercapacitors. Journal of Power Sources.

Authors unavailable. The optimal integrating state of VOx with the synergistic effect of Cu²⁺ cation and polyaniline for high-performance flexible fiber zinc-ion battery. Journal of Energy Storage.