Shamsa Waheed

University of Engineering and Technology Taxila

Papers

Total Citations

H-Index

About

Shamsa Waheed is a rising researcher in the field of artificial intelligence and computer vision, with a primary focus on human action recognition and deep learning. Her most-cited work, "An Automated Human Action Recognition and Classification Framework Using Deep Learning" (2023), has already garnered 8 citations, demonstrating early impact in a rapidly evolving domain. In this paper, she addresses the critical challenge of automating the identification of human activities using sensor data, with direct applications in smart home healthcare systems—particularly for enhancing patient rehabilitation. By leveraging deep learning architectures, Waheed’s framework offers a robust solution for classifying complex human movements, bridging the gap between raw sensor inputs and actionable insights. Her contributions are especially notable for their potential to improve quality of life through non-intrusive monitoring technologies. As an emerging scholar, Waheed’s work signals a promising trajectory in applied AI, where her research not only advances technical methodologies but also addresses real-world healthcare needs. With a growing citation footprint and a focus on impactful applications, she is poised to become a key contributor to the intersection of deep learning and assistive technology.