Haifa F. Alhasson
Papers
3
Total Citations
42
H-Index
3
About
Haifa F. Alhasson is a rising researcher at the forefront of artificial intelligence and computer vision, with a focus on deep learning for scene understanding, human activity recognition, and ubiquitous computing. Her work bridges the gap between high-level semantic interpretation and real-world applications, from indoor scene recognition to dynamic group behavior analysis. In her highly cited 2025 paper on multimodal scene recognition, she tackles the complexity of indoor environments by integrating semantic segmentation with deep learning, achieving robust scene interpretation despite cluttered and varied features. Her research on dynamic graph neural networks for UAV-based group activity recognition in structured team sports addresses challenges like occlusions and dynamic interactions, advancing autonomous systems and surveillance. Additionally, her deep learning framework for healthy lifestyle monitoring and outdoor localization demonstrates practical impact in healthcare and personal safety, combining locomotion recognition with environmental awareness. With over 40 citations across her top publications in a single year, Alhasson’s innovative methodologies are quickly gaining traction, marking her as a promising contributor to AI-driven scene and activity analysis.
Research Focus
Key Achievements
Top Papers
- 1
- 2
- 3