Shekhar Gupta
Papers
1
Total Citations
3
H-Index
1
About
Shekhar Gupta is a researcher specializing in human motion prediction and deep learning architectures, with a focus on advancing human-robot interaction and assistive technologies. His most notable contribution is the development of a novel motion prediction strategy using an inception residual block, detailed in his 2023 paper, which has garnered 3 citations. This work integrates inception modules with residual connections to enhance the accuracy and efficiency of forecasting human movements, addressing critical challenges in real-time applications such as autonomous systems and rehabilitation robotics. Gupta’s research bridges computer vision and machine learning, offering scalable solutions for dynamic environments. While his citation count is still growing, his innovative approach has been recognized for its potential to improve safety and responsiveness in human-centered AI systems. His achievements highlight a promising trajectory in computational modeling, with implications for fields like sports analytics and elderly care. Gupta’s work continues to inspire further exploration into robust, real-time prediction frameworks.
Research Focus
Key Achievements
Top Papers
- 1