Prathamesh Samal

Thapar Institute of Engineering & Technology

Papers

Total Citations

H-Index

About

Prathamesh Samal is a researcher at the forefront of human-robot interaction (HRI), specializing in the application of deep learning to activity recognition. His work bridges the gap between computational intelligence and real-world robotic systems, with a primary focus on enabling robots to understand and respond to human behavior in dynamic environments. Samal’s most cited paper, "DL-DARE: Deep learning-based different activity recognition for the human–robot interaction environment" (2023), introduces a novel framework that leverages deep neural networks to classify diverse human actions, enhancing the safety and fluidity of collaborative robotics. This work has already garnered 8 citations, signaling its growing influence in the field. By tackling the challenge of robust activity recognition in noisy, unstructured settings, Samal contributes to the development of more intuitive and adaptive robotic assistants. His research holds promise for applications in manufacturing, healthcare, and service robotics, where seamless human-robot teamwork is critical. As an emerging voice in HRI, Samal’s work is paving the way for smarter, more responsive machines that can learn from and adapt to their human counterparts.