Rozana Ghandy | Digital Data | Best Researcher Award

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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

Wentao Chen | Data Analysis | Research Excellence Award

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Mr. Wentao Chen | Data Analysis | Research Excellence Award

Nanjing University of Information Science and Technology | China

Mr. Wentao Chen is a dedicated geography researcher currently pursuing a master’s degree with a strong academic foundation in geographical science, remote sensing, and spatial data analysis. Building upon his undergraduate training in earth science, geomorphology, meteorology, ecology, and GIS, he has developed a solid interdisciplinary background that supports his growing expertise in coastal and environmental studies. His research experience includes participation in major national projects, such as investigations into coastline evolution under global change and studies on carbonate leaching processes and carbon sequestration in coastal soil chronosequences. As the first author of a peer-reviewed article in Remote Sensing, he contributed significant insights into tidal mudflat sediment-thickness identification using ground-penetrating radar, demonstrating improved methodological accuracy through advanced signal-processing techniques. His academic performance has been recognized with multiple scholarships and awards, reflecting consistent commitment and scholarly potential. His primary research interests lie in coastal geomorphology, environmental remote sensing, and GIS-based spatial analysis, with a particular focus on coastal dynamic processes and subsurface structural characterization. Continually motivated to expand his technical and research capabilities, he aims to contribute meaningful scientific understanding to the fields of coastal environmental change and geospatial technology.

Profile : Orcid

Featured Publication

Chen, W., Zhao, C., Zheng, G., Zhu, J., & Li, X. (2025). “Identification of the Sediment Thickness Variation of a Tidal Mudflat in the South Yellow Sea via GPR.” Remote Sensing.

 

Hongyan Jin | Bioinformatics | Young Researcher Award

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Ms. Hongyan Jin | Bioinformatics | Young Researcher Award

Tarim University | China

Ms. Hongyan Jin dedicated and accomplished biologist with a strong foundation in plant molecular biology, bioinformatics, and physiological research. Holds a Master’s degree in Biology from Tarim University, with a cumulative GPA of 87.64, earning recognition as an Outstanding Graduate and recipient of multiple university-level scholarships. Academic training includes advanced courses in plant physiology, molecular and cell biology, biochemistry, bioinformatics, and biostatistics. Experienced in genome-wide identification and analysis of gene families, particularly the SnRK2 gene family in Populus euphratica, and proficient in total RNA extraction and qRT-PCR techniques. Research focuses on plant responses to abiotic stresses, integrating computational and experimental approaches to explore stress-responsive gene functions. Published research in the International Journal of Molecular Sciences, highlighting expertise in genome-wide bioinformatics analysis and molecular plant biology. Fluent in English (CET-6) and holds a Mandarin proficiency certificate, demonstrating strong communication skills. Recognized for academic excellence, diligence, and integrity, with a proactive and detail-oriented approach to research and professional responsibilities. Committed to continuous learning and tackling scientific challenges with rigor and persistence. Possesses a clear understanding of professional knowledge, strong integrative abilities, and a collaborative mindset, making significant contributions to plant biology and stress response research.

Profile : Scopus

Featured Publications

(2025). The identification and characterization of the PeGRF gene family in Populus euphratica Oliv. heteromorphic leaves provide a theoretical basis for the functional study of PeGRF9. International Journal of Molecular Sciences.

(2025). Genome-Wide Identification of the SnRK2 Gene Family and Its Response to Abiotic Stress in Populus euphratica

(2024).Comparative Genomics Analysis of the Populus Epidermal Pattern Factor (EPF) Family Revealed Their Regulatory Effects in Populus euphratica Stomatal Development

Hugo Hervé-Côte – Machine Learning and AI Applications – Best Researcher Award 

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Mr. Hugo Hervé-Côte - Machine Learning and AI Applications - Best Researcher Award 

Ecole de Technologie Supérieure - Canada 

Author Profile

Early Academic Pursuits

Mr. Hugo Hervé-Côté embarked on his academic journey with a strong foundation in mechanical and industrial engineering. He began his education at the prestigious Ecole Nationale Supérieure des Arts et Métiers (ENSAM) in Angers, France, where he pursued a Diploma in Mechanical, Industrial, and Energy Engineering. During his time at ENSAM, from September 2019 to July 2021, Hugo honed his expertise in various engineering disciplines, setting the stage for his future endeavors in artificial intelligence and machine learning.

Following his graduation from ENSAM, Hugo continued to build on his technical knowledge and skills by pursuing a Master's degree in Automated Production Engineering (M.Sc.A) at the Ecole de Technologie Supérieure (ETS) in Montreal, Canada. From September 2021 to December 2023, he delved deeper into advanced engineering concepts and specialized in machine learning and computer vision. This dual-degree experience equipped him with a robust academic background and practical skills, making him a versatile engineer ready to tackle complex challenges in the industry.

Professional Endeavors

Mr. Hugo's professional journey has been marked by significant contributions to the fields of non-destructive testing (NDT) and industrial inspection. His career began with a notable role as an Artificial Intelligence Engineer at EddyFi Technologies in Quebec, Canada, from December 2023 to March 2024. In this position, Hugo focused on the development and implementation of machine learning models for analyzing eddy current images in non-destructive testing. He was instrumental in creating a user-friendly interface for visualizing and labeling complex magnetic data, and he developed a comprehensive data pipeline for training, validating, and testing machine learning models. His work culminated in a proof of concept that demonstrated the effectiveness of these models in real-world applications.

Prior to his role at EddyFi Technologies, Hugo gained valuable experience as a Student Researcher in Ultrasonic Inspection using Machine Learning at ETS and in collaboration with Nucleom. From September 2021 to December 2023, he worked on detecting defects in ultrasonic images, developing a standardized database for ultrasonic imaging, and addressing industrial challenges through regular project progress meetings with Nucleom and EddyFi. His efforts contributed to the advancement of ultrasonic inspection techniques and the integration of machine learning in this domain.

Contributions and Research Focus

Mr. Hugo's research focus has been centered on the application of machine learning and artificial intelligence in non-destructive testing and industrial inspection. His master's thesis involved the development of a tool for analyzing ultrasonic images using machine learning. This project, conducted from September 2021 to December 2023, included the acquisition of defect data from welds using Full Matrix Capture (FMC) and the development of algorithms for image reconstruction and defect detection. Hugo also created a significant labeled database of over 100,000 images, which served as a foundation for training deep learning models. His work was presented at conferences such as OnDuty in Windsor, ON (2022) and Toronto, ON (2023), and was published in the scientific journal Ultrasonics.

Hugo's research contributions extend to developing post-processors for CNC machines and designing cryogenic tool mounts. His projects have involved the practical application of engineering principles to solve real-world problems, demonstrating his ability to bridge the gap between theory and practice.

Accolades and Recognition

Mr. Hugo Hervé-Côté's work has been recognized both academically and professionally. His publication in Ultrasonics, titled "Automatic flaw detection in sectoral scans using machine learning," has garnered attention in the scientific community, showcasing his expertise in applying advanced technologies to improve industrial inspection processes. This publication is a testament to his dedication to research and innovation in the field of non-destructive testing.

Throughout his academic and professional career, Hugo has demonstrated excellence in his field, earning the respect of his peers and supervisors. His involvement in various projects and his ability to present his findings at conferences highlight his commitment to advancing knowledge and contributing to the engineering community.

Impact and Influence

Mr. Hugo's work has had a significant impact on the field of non-destructive testing and industrial inspection. By integrating machine learning techniques into traditional inspection methods, he has contributed to the development of more accurate and efficient defect detection processes. His research on ultrasonic imaging and eddy current testing has the potential to revolutionize how industries approach quality control and maintenance, leading to safer and more reliable infrastructure.

Hugo's contributions have also influenced the development of standardized databases and formats for storing and analyzing inspection data, facilitating collaboration and knowledge sharing among researchers and industry professionals. His efforts to create user-friendly interfaces and data pipelines have made advanced technologies more accessible to engineers and technicians, promoting the adoption of machine learning in industrial applications.

Legacy and Future Contributions

Mr. Hugo Hervé-Côté's legacy lies in his innovative approach to solving complex engineering problems through the application of machine learning and artificial intelligence. His work has paved the way for future advancements in non-destructive testing and industrial inspection, setting a high standard for integrating cutting-edge technologies into practical applications.

Looking ahead, Hugo's future contributions are likely to continue shaping the field of engineering. His strong foundation in mechanical and industrial engineering, combined with his expertise in artificial intelligence, positions him as a leader in the development of next-generation inspection techniques. As industries increasingly rely on data-driven solutions, Hugo's work will remain at the forefront of technological innovation, driving progress and improving safety and efficiency across various sectors.

Notable Publication