Garima Aggarwal

Papers

Total Citations

H-Index

About

Garima Aggarwal is an emerging researcher whose work sits at the intersection of deep learning, computer vision, and intelligent systems. Her research focuses on human activity recognition, a critical area enabling advancements in robotics, the Internet of Things (IoT), and smart environments. In her most notable work, "Analysis of Human Activity Recognition using Deep Learning" (2021), Aggarwal conducts a rigorous comparative analysis of deep learning methodologies applied to activity recognition tasks, providing valuable benchmarks for researchers and practitioners navigating the rapidly expanding data landscape of modern technology. This paper has garnered 15 citations, reflecting its utility as a reference point for those entering or advancing within this specialized field. Her contributions are particularly timely, as the proliferation of connected devices and autonomous systems demands robust, accurate methods for interpreting human behavior in real time. Aggarwal's research serves as a foundational resource for students and engineers working to bridge the gap between raw sensor data and meaningful human-centered intelligence, positioning her as a promising voice in the evolving conversation around AI-driven perception and human-machine interaction.