Nidhi Dua

National Institute of Technology Jamshedpur

Papers

Total Citations

238

H-Index

About

Nidhi Dua is a leading researcher at the intersection of artificial intelligence, robotics, and human motion analysis. Her work focuses on developing advanced deep learning architectures for human activity recognition (HAR) and bipedal locomotion. Dua's most impactful contribution is her "Inception inspired CNN-GRU hybrid network for human activity recognition" (2022, 146 citations), which pioneered a novel fusion of convolutional and recurrent neural networks to capture both spatial and temporal features in human movement data. She further advanced the field with an optimized deep learning model using inertial measurement units (2023, 40 citations), addressing key challenges in real-world HAR applications like healthcare and human-robot interaction. In robotics, Dua developed an "Optimized-LSTM and RGB-D Sensor-Based Human Gait Trajectory Generator for Bipedal Robot Walking" (2022, 52 citations), enabling more natural, human-like locomotion in bipedal robots—a critical step for applications in manufacturing, rehabilitation, and assistive technologies. Her work demonstrates how deep learning can bridge the gap between human movement analysis and robotic control, with her citation record reflecting the growing importance of these methods in both academic and applied settings.