Ardhendu Behera
Papers
2
Total Citations
58
H-Index
2
About
Ardhendu Behera’s research lies at the intersection of computer vision, human-robot interaction, and intelligent healthcare systems. He is best known for advancing human activity recognition through deep learning, notably with his work on “Attentional Learn-able Pooling for Human Activity Recognition” (2021), which introduced a novel attention-based mechanism to improve the classification and prediction of human behaviors—critical for enabling robots to anticipate and respond to human actions in real time. His contributions extend to the ethical and practical deployment of robotic technologies in palliative and supportive care. In his highly cited 2019 paper, “Robotic technology for palliative and supportive care: Strengths, weaknesses, opportunities and threats” (53 citations), Behera provides a balanced SWOT analysis that has become a foundational reference for researchers exploring the safe integration of assistive robots in end-of-life and elderly care settings. By combining technical innovation with critical socio-technical evaluation, Behera’s work has shaped both the algorithms that power intelligent robots and the frameworks that guide their responsible use in sensitive healthcare environments.
Research Focus
Key Achievements
Top Papers
- 1
- 2Attentional Learn-able Pooling for Human Activity Recognition5 citations · 2021