Mohamed Helmy | Modeling | Research Excellence Award

Published on by Composite Awards

Mohamed Helmy | Modeling | Research Excellence Award

Dr. Mohamed Helmy at university of saienza | Italy

Mohamed Helmy is a Ph.D. researcher in geodesy, hydrography, Earth observation, and remote sensing, with a strong focus on sea-level analysis and tidal modeling. His research integrates in situ measurements, satellite data, and numerical simulations to improve tidal datum realization and coastal monitoring. He has published studies on tidal characteristics in major harbors across Egypt and the Middle East, supporting maritime safety and coastal management. In parallel, he applies deep learning and transformer-based models to enhance digital terrain models and crop classification accuracy. His work demonstrates interdisciplinary expertise in geospatial analysis, machine learning, and environmental applications.

Citation Metrics (Google Scholar)

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Featured Publications

Wenyan Wu | Modeling | Best Researcher Award

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Wenyan Wu | Modeling | Best Researcher Award

Dr. Wenyan Wu at Guangdong University of Technology | China

Dr. Wenyan Wu is an emerging researcher whose work focuses on the intersection of artificial intelligence, multimodal learning, and intelligent systems with applications in emotion recognition, sentiment analysis, and human-computer interaction. Since creating her ORCID record in August 2022, Dr. Wu has actively contributed to advancing research in cross-modal data analysis, integrating deep learning frameworks with cognitive and affective computing techniques. Her recent publication, “Modality-Enhanced Multimodal Integrated Fusion Attention Model for Sentiment Analysis” (Applied Sciences, 2025), introduces a novel attention-based fusion approach to improve sentiment analysis accuracy by effectively capturing inter-modal dependencies across text, audio, and visual cues. In “Collaborative Analysis of Learners’ Emotional States Based on Cross-Modal Higher-Order Reasoning” (Applied Sciences, 2024), Dr. Wu explores emotion-aware learning environments, presenting innovative reasoning mechanisms for identifying and analyzing learners’ affective states to enhance adaptive education systems. Her research on “Mask-Wearing Detection in Complex Environments Based on Improved YOLOv7” (Applied Sciences, 2024) demonstrates her interdisciplinary expertise, combining computer vision and deep neural networks to address real-world safety monitoring challenges. Earlier, her foundational study, “A Novel Method for Cross-Modal Collaborative Analysis and Evaluation in the Intelligence Era” (Applied Sciences, 2022), laid the groundwork for her later research by proposing an integrated model for data collaboration across modalities in intelligent environments. Dr. Wu’s scholarly output reflects her strong analytical and technical acumen, emphasizing multimodal integration, attention mechanisms, and deep learning optimization. Her contributions not only advance theoretical understanding but also provide practical frameworks for developing emotionally intelligent and context-aware AI systems, bridging the gap between computational models and human-centered design in modern intelligent applications.

Profile: Orcid 

Featured Publications 

Salem Brahim | Modeling | Best Researcher Award

Published on by Composite Awards

Salem Brahim | Modeling | Best Researcher Award

Dr. Salem Brahim, Institut Supérieur des Etudes Technologiques de Gafsa, Tunisia.