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Chang Liu | Digital Data | Research Excellence Award

Published on by Research Data Analysis

Mr. Chang Liu | Digital Data | Research Excellence Award

 Xi ’ an University of Posts & Telecommunications Shaanxi | China

Mr. Chang Liu is a researcher specializing in data analysis and its application in the digital economy, enterprise value creation, and policy evaluation. He holds advanced degrees in economics and finance, and has contributed extensively to academic research, national-level projects, and provincial research initiatives. His expertise encompasses the full data analysis workflow, including data collection, cleaning, modeling, and empirical verification, with proficiency in Python, STATA, and SPSS. He has co-authored multiple SSCI and PKU Core papers focusing on digital finance, enterprise digital transformation, ESG impact, and the role of data elements in promoting new quality productive forces. In addition, he has led key data analysis tasks in projects evaluating corporate performance, large model spillovers, digital asset accounting, and the internal transmission mechanism of the digital economy. His research integrates advanced econometric methods, spatial models, panel regressions, and complex system coordination frameworks to ensure robust and scientifically reliable conclusions. Through practical work, including enterprise audits and data asset evaluations, he has applied analytical techniques to real-world problems, producing actionable insights. Mr. Liu’s work demonstrates a commitment to precision, academic rigor, and the advancement of data-driven research, contributing significantly to both theoretical understanding and practical application in the field of digital economy and enterprise innovation.

Profile : Orcid

Featured Publication

How data elements fuel new quality productive forces in enterprises: A perspective from digital finance, 2026

Lulu Fu | Healthcare Data Analysis | Research Excellence Award

Published on by Research Data Analysis

Dr. Lulu Fu | Healthcare Data Analysis | Research Excellence Award

The Second Hospital of Jilin University | China

Dr. Lulu Fu is a researcher in reproductive medicine at the Reproductive Medical Center and the Jilin Provincial Key Laboratory of Reproductive Biology, The Second Hospital of Jilin University, where she focuses on assisted reproductive technologies and the pathophysiology of female reproductive disorders. She earned her Ph.D. and master’s degrees in obstetrics and gynecology from Jilin University, following a bachelor’s degree in clinical medicine from Taishan Medical College. Since 2018, she has worked as a reproductive medicine specialist, contributing to both clinical services and academic research. Her clinical and scientific interests include ART, polycystic ovary syndrome, premature ovarian insufficiency, endometriosis, recurrent pregnancy loss, and epithelial–mesenchymal transition mechanisms. She has published multiple peer-reviewed studies, including systematic reviews, meta-analyses, and translational research on ovarian function, reproductive immunology, and molecular biomarkers. Her work also explores the relationship between microbial metabolites and reproductive health, as well as novel therapeutic approaches in infertility management. Through collaborations with multidisciplinary teams, she aims to improve diagnostic and therapeutic strategies for women’s reproductive endocrine disorders. Her career reflects a commitment to advancing reproductive biology and supporting evidence-based assisted reproductive practices that strengthen clinical outcomes for patients.

Profile : Orcid

Featured Publications

Wang, M., Zheng, L., Ma, S., Xu, Y., Zhang, J., & Fu, L. (2025). A comparison of the effects of progestin-primed ovarian stimulation protocol and gonadotropin-releasing hormone antagonist protocol in assisted reproductive technology: a systematic review and meta-analysis. Journal of Assisted Reproduction and Genetics.

Yan, J., Zheng, L.-w., Xu, Y., Chu, X.-m., Zhang, J.-s., Zhang, X.-y., Liang, Y., Liu, S.-s., & Fu, L.-l. (2025). The role of granulocyte–macrophage colony-stimulating factor in female assisted reproductive technology treatment: a systematic review and meta-analysis. Journal of Assisted Reproduction and Genetics.

Jiabao Li | Engineering | Research Excellence Award

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Mr. Jiabao Li | Engineering | Research Excellence Award

Yangzhou University | China

Mr. Jiabao Li is a materials scientist and electrochemical energy researcher specializing in sodium-ion batteries and capacitive deionization, with particular focus on electrode and electrolyte design for extreme temperature environments. He earned his bachelor’s and master’s degrees in applied chemistry from Anhui Agricultural University, followed by a Ph.D. in materials and optoelectronics from East China Normal University, including a joint research period at the Georgia Institute of Technology. Since completing his doctoral work, he has served as a lecturer and researcher, leading multiple competitive research projects in materials innovation and energy-storage systems. His work integrates experimental synthesis with computational tools such as DFT modeling and molecular dynamics simulations to advance high-performance sodium-ion storage materials. He has published 98 scientific documents, accumulating 5,410 citations across 4,235 referencing documents, with an h-index of 40, reflecting significant global impact in the fields of battery chemistry and electrochemical engineering. His awards include national and institutional scholarships that recognize excellence in scientific research and academic achievement. Overall, his career demonstrates sustained contributions to next-generation energy-storage technologies and the advancement of robust sodium-ion systems for low-temperature and high-efficiency applications.

Profile : Scopus

Featured Publications

Unveiling the neglected role of oxygen doping in nitrogen-doped carbon for enhanced capacitive deionization performance. Nature Communications, 2025.

Rapidly evaluating electrochemical performance of transition metal disulfides for lithium-ion batteries using machine learning classifier. Chemical Engineering Journal, 2025.

Ionic conductor-armored Li₃V₂(PO₄)₃: a robust electrode for lithium capture via capacitive desalination. Chemical Communications, 2025.

Anion screening in ether-based electrolytes for boosted sodium storage at low temperature. Energy Storage Materials, 2025.

Coordination-tuned Na₃V₂(PO₄)₃ cathodes for low-temperature sodium-ion batteries. Chemical Communications, 2025.

 

Rozana Ghandy | Digital Data | Best Researcher Award

Published on by Research Data Analysis

Dr. Rozana Ghandy | Digital Data | Best Researcher Award

 Islamic Azad University, Tehran | Iran

Dr. Rozana Ghandy is an academic researcher in physical oceanography, pursuing doctoral studies at the Science and Research Branch of Islamic Azad University, where her work focuses on analyzing heat fluxes over the North Indian Ocean and the Persian Gulf using advanced weather reanalysis datasets. She holds a master’s degree in oceanography from Islamic Azad University, North Tehran Branch, where she investigated geostrophic currents through field measurements and satellite observations, and a bachelor’s degree in science from Isfahan University. With extensive teaching experience across multiple educational levels—including physics instruction at pre-university, high-school, and laboratory settings—she has contributed significantly to academic development and educational leadership. Her research interests include air–sea interactions, ocean circulation, climate variability, regional sea dynamics, and the application of remote sensing in marine studies. She has presented and published studies on physical parameters in coastal regions, surface flux behavior, and standardized approaches to air–sea heat flux assessment across key marine basins. Her academic achievements include competitive rankings in national entrance examinations and scholarships recognizing her scientific potential. Overall, her work reflects a dedication to advancing understanding of ocean–atmosphere processes and contributing to the broader field of marine and climate science.

Profile : Orcid

Featured Publication

Study of surface fluxes over the Northern Indian Ocean Seas, 2023

Fangdi Ye | Offshore Wind Power | Research Excellence Award

Published on by Research Data Analysis

Mr. Fangdi Ye | Offshore Wind Power | Research Excellence Award

Zhejjiang Provincial Energy Group Company Ltd | China

Mr. Fundi is an accomplished energy-sector professional associated with Zhejiang Provincial Energy Group Company Ltd., where he contributes to the advancement of China’s offshore wind power initiatives. He holds an academic background in engineering and renewable energy management, building a solid foundation for his work in large-scale clean-energy development. Throughout his career, he has gained extensive experience in project planning, offshore infrastructure deployment, and strategic energy transition programs, working on initiatives that support regional sustainability goals and national carbon-neutral ambitions. His professional interests include offshore turbine technology, grid integration, marine environmental impact assessment, and the long-term scalability of renewable energy systems. Mr. Fundi has participated in collaborative research efforts with academic and industry partners, focusing on innovation in offshore wind operations and maintenance. He has been recognized within the sector for his contributions to technology modernization and efficiency improvements in coastal wind projects. His ongoing work reflects a commitment to accelerating the deployment of clean, reliable energy resources while promoting responsible environmental stewardship. Overall, Mr. Fundi’s career illustrates a forward-looking vision centered on renewable-energy innovation and the strategic development of China’s offshore wind power capabilities.

Profiles : Scopus | Orcid

Featured Publications

Xiao, T., Lian, J., Ye, F., Xiong, D., & Hao, X. (2024). Experimental and numerical study on motion characteristics of a bucket foundation during immersion process. Ocean Engineering. https://doi.org/10.1016/j.oceaneng.2024.117782

Ye, F., Lian, J., Xiao, T., Xiong, D., Wang, H., Guo, Y., & Shao, N. (2024). Behavior Analysis of a Bucket Foundation with an Offshore Wind Turbine during the In-Water Sinking Process. Journal of Marine Science and Engineering. https://doi.org/10.3390/jmse12030494

Ye, F., Lian, J., Xiong, D., Wang, H., Guo, Y., Wang, P., & Xiao, T. (2023). Effects of damping plate on the motion response of transport ships under waves. Applied Ocean Research. https://doi.org/10.1016/j.apor.2023.103507

Lian, J., Ye, F., Wang, P., Guo, Y., Wang, H., Xiao, T., & Xiong, D. (2023). Integrated transportation of offshore wind turbine and bucket foundation based on a U and K shaped assembled platform. Ocean Engineering. https://doi.org/10.1016/j.oceaneng.2023.114096

Ye, F.-D., Lian, J.-J., Guo, Y.-H., Wang, H.-J., Xiao, T.-R., Xiong, D.-Z., & Yu, T.-S. (2023). Stability Study on the Bucket Foundation with Multi-Compartment During the Floating-up Process Considering Air Compressibility. China Ocean Engineering. https://doi.org/10.1007/s13344-023-0081-8

Fan Xiao | Data Processing | Research Excellence Award

Published on by Research Data Analysis

Assoc. Prof. Dr. Fan Xiao | Data Processing | Research Excellence Award

Sun Yat-sen University | China

Xiao Fan is an Associate Professor and PhD advisor at the School of Earth Sciences and Engineering, Sun Yat-sen University, recognized for his contributions to mineral exploration, mathematical geoscience, and data-driven Earth system analysis. He received his bachelor’s and doctoral degrees in mineral resource exploration from China University of Geosciences (Wuhan), with joint doctoral training at the University of Ottawa. His research focuses on mineral system modeling, multi-physics numerical simulation, fractal and singularity analysis, machine-learning-based mineral prospectivity, and knowledge-driven geoscientific data integration. As a core member of major national innovation teams, he has led or participated in several national and provincial research projects and contributed to the creation of an advanced UAV-based geophysical–geochemical acquisition and processing platform. He has published 54 documents with 986 citations from 706 sources and holds an h-index of 19, along with multiple patents, software copyrights, and highly cited works in leading SCI journals. He serves on editorial boards and scientific committees, including roles as youth editor and guest editor, and has organized sessions for the International Geological Congress. His work advances quantitative mineral prediction and computational geoscience, contributing impactful models and methods that enhance understanding of mineralization processes and exploration efficiency.

Profiles : Scopus | Orcid

Featured Publications

(2025). “Three-Dimensional Prospectivity Modeling of Jinshan Ag-Au Deposit, Southern China by Weights-of-Evidence.” Journal of Earth Science.

(2025). “Lithologic mapping of intermediate-acid intrusive rocks in the eastern Tianshan Gobi Desert using machine learning and multi-source data fusion.” Earth Science Frontiers.

(2025). “A DFT study on mechanisms of indium adsorption on sphalerite (100), (110), and (111) surfaces: Implications for critical metal mineralization.” Ore Geology Reviews.

(2025). “Data-driven expeditious mapping and identifying granites in covered areas via deep machine learning: A case study on the implications for geodynamics and mineralization of Eastern Tianshan.” Lithos.

(2025). “Numerical Modeling and Exploration Data Coupled-driven Mineral Prospectivity Mapping: A Case Study of Fankou Pb-Zn Deposit.” Geotectonica et Metallogenia.

Bardia Rodd | Machine Learning and AI Applications | Best Researcher Award

Published on by Research Data Analysis

Prof. Bardia Rodd | Machine Learning and AI Applications | Best Researcher Award

SUNY Upstate Medical University | United States

Prof. Bardia Rodd is an Associate Professor at SUNY Upstate Medical University and Associate Director of AI Innovation at the AI for Health Equity, Analytics, and Diagnostics (AHEAD) Center. He completed dual PhDs in Electrical & Computer Engineering from Université Laval and in Computer Science from the University of Malaya, alongside a postdoctoral fellowship at the University of Pennsylvania Perelman School of Medicine, focusing on precision medicine, artificial intelligence, and image-guided systems. His academic career spans faculty positions at SUNY Upstate, the University of Maryland, and Laval University, with extensive experience in biocomputational engineering, machine learning, medical image analysis, and data-driven healthcare solutions. He has led numerous grants, including initiatives in AI in education, biomedical research, and curriculum development. Prof. Rodd has supervised multiple graduate and postgraduate students and contributed to open educational resources, advancing accessible teaching in machine learning and bioengineering. He is an active member of professional societies including IEEE, SPIE, and the Association of Pathology Informatics, serving on multiple technical committees and leadership roles. His research interests include AI-driven biomedical imaging, predictive modeling, and health equity applications. Prof. Rodd has authored a textbook on machine learning for data analysis and continues to integrate research, teaching, and innovation to advance computational medicine and AI education.

Profile : Scopus

Featured Publications

Siezen, H., Awasthi, N., Rad, M. S., Ma, L., & Rodd, B. (2025). “Low-rank distribution embedding of dynamic thermographic data for breast cancer detection.” Journal of Thermal Biology, 104303.

Usamentiaga, R., Fidanza, A., Yousefi, B., Iacutone, G., Logroscino, G., & Sfarra, S. (2025). “Advancing knee injury prevention and anomaly detection in rugby players through automated processing of infrared thermography: A novel biothermodynamics approach.” Thermal Science and Engineering Progress, 103782.

Rad, M. S., Huang, J. V., Hosseini, M. M., Choudhary, R., Siezen, H., Akabari, R., et al. (2025). “Deep learning for digital pathology: A critical overview of methodological framework.” Journal of Pathology Informatics, 100514.

Yousefi, B., Khansari, M., Trask, R., Tallon, P., Carino, C., Afrasiyabi, A., Kundra, V., Ma, L., Ren, L., Farahani, K., & Hershman, M. (2025). “Measuring subtle HD data representation and multimodal imaging phenotype embedding for precision medicine.” IEEE Transactions on Instrumentation and Measurement, TIM-24-01821.

Cao, Y., Sutera, P., Mendes, W. S., Yousefi, B., Hrinivich, T., Deek, M., et al. (2024). “Machine learning predicts conventional imaging metastasis-free survival (MFS) for oligometastatic castration-sensitive prostate cancer (omCSPC) using prostate-specific membrane antigen (PSMA) PET radiomics.” Radiotherapy and Oncology, 199, 110443.

Khalid Alanazi | Engineering | Research Excellence Award

Published on by Research Data Analysis

Dr. Khalid Alanazi | Engineering | Research Excellence Award

Department of Mechanical Engineering/University of Tabuk | Saudi Arabia

Dr. Khalid Alanazi is an Assistant Professor of Mechanical Engineering at the University of Tabuk, specializing in energy systems, fluid mechanics, and material erosion studies. He earned his B.Sc. in Mechanical Engineering with distinction from the University of Tabuk, followed by M.Sc. and Ph.D. degrees from the University of Tulsa, where he conducted extensive research on solid particle erosion, oil-water emulsions, and computational fluid dynamics. Over his academic career, Dr. Alanazi has contributed to both teaching and curriculum development, instructing courses ranging from Engineering Mechanics and Fluid Mechanics to Turbomachinery and Refrigeration Systems, while supervising senior design projects and field training programs. His research primarily focuses on solar-powered desalination technologies, oil-water emulsion behavior under variable conditions, and the erosion resistance of metals in gas-solid flows. Dr. Alanazi has published numerous papers in high-impact journals and presented at international conferences, reflecting his commitment to advancing both fundamental and applied mechanical engineering. Recognized for his academic excellence, he has received multiple awards including the Prince Fahad bin Sultan Award for Academic Excellence and the Chapman Graduate Scholar Presentation Awards. His work continues to bridge experimental, computational, and applied approaches, contributing to sustainable engineering solutions and industrial applications worldwide.

Profile : Google Scholar

Featured Publications

Alanazi, K., Mohan, R. S., Kolla, S. S., & Shoham, O. (2024). “Effects of water salinity and temperature on oil-in-water emulsions stabilized by a nonionic surfactant.” Journal of Molecular Liquids, 414, 126067.

Alanazi, K., Mohan, R., Kolla, S. S., & Shoham, O. (2023). “Experimental study of monovalent salt and hydrochloric acid solution effects on the stability of blank oil-water dispersion in batch separators.” ASME International Mechanical Engineering Congress and Exposition, 87660.

Alanazi, K., Mohan, R., Kolla, S. S., & Shoham, O. (2023). “Effect of water cut and temperature on the stability of emulsifier-free oil-water dispersion in batch separators at various stirrer speeds.” ASME International Mechanical Engineering Congress and Exposition, 87660.

AbdelMeguid, H., Alanazi, K., Al-Shammari, A. F., Al-Twaim, O., Aljuhani, A., et al. (2025). “Sequential thermal and optical upgrades for passive solar stills: Toward sustainable desalination in arid climates.” Clean Energy and Sustainability, 3(4), 10017.

Alanazi, K., Mohan, R., Kolla, S. S., & Shoham, O. (2025). “Stability analysis of pure oil-water emulsion in gravity-based separators.” Journal of Fluids Engineering, 147(1), 011401.

Xiaochen Xie | Quantitative Research | Research Excellence Award

Published on by Research Data Analysis

Dr. Xiaochen Xie | Quantitative Research | Research Excellence Award

Renmin University of China | China

Dr. Xiaochen Xie is an Assistant Professor at the School of Finance, Renmin University of China, with concurrent research associate positions at the China Financial Policy Research Center, the Institute of Public Finance and Taxation, and the Institute of Digital Economics and Taxation. He holds a Ph.D. in Economics from Pennsylvania State University, an M.S. in Economics from the University of Wisconsin–Madison, and dual B.E. in Finance and B.S. in Statistics from Peking University. His research spans international trade, industrial organization, public economics, and urban economics, with a focus on firm entry, pricing strategies, and the economic impacts of policy interventions. Dr. Xie has published in leading journals, including the Journal of Economic Geography, and has multiple working papers under review in top-tier journals. He has received awards such as Outstanding Young Scholar at Renmin University and recognition for outstanding papers at the NCER-CCER Chinese Economy Conference. Dr. Xie has extensive teaching experience in undergraduate and graduate courses on public finance, quantitative empirical economics, and structural methods. His research integrates empirical and structural approaches to inform trade, fiscal, and industrial policies. Dr. Xie’s work contributes to understanding the intersection of market structure, policy design, and economic welfare, influencing both academic research and practical policy-making.

Profiles : Orcid | Google Scholar

Featured Publications

Chen, Y., Huang, T., & Xie, X. (2025). “Place-based policies: First-mover advantage and persistence.” Journal of Economic Geography, lbaf001.

Lu, W., & Xie, X. (2024). “Trade, markups, and consumer welfare: Evidence from the global smartphone industry.” Available at SSRN 4804811.

Xie, X. (2021). Two essays on firm entry and pricing. The Pennsylvania State University.