Papers
7
Total Citations
58
H-Index
3
About
Manoj Ramanathan is a leading researcher in human-robot interaction (HRI), social robotics, and explainable AI, whose work bridges the gap between human intent and robotic action. His most notable contribution is the development of the Nadine Humanoid Social Robotics Platform (2019, 25 citations), a pioneering system that explores how humanoid robots can function as organizational workforce members, leveraging sentiment analysis to assess their social acceptance. Ramanathan’s experimental study on the uncanny valley effect for interactive social agents (2022, 19 citations) provides critical insights into user discomfort with near-human robots, informing design principles for more natural HRI. His recent work, ExTraCT (2024, 6 citations), introduces explainable trajectory corrections using textual feature descriptions, enabling robots to adapt to user language inputs without extensive retraining—a breakthrough for intuitive, generalizable HRI. Additionally, his research on human posture detection using H-ELM (2016, 3 citations) and robotic wheelchair docking systems (2025, 1 citation) demonstrates a commitment to assistive robotics. With over 58 total citations, Ramanathan’s interdisciplinary approach—combining robotics, AI, and psychology—positions him as a key figure in making robots more socially adept and user-friendly for real-world applications.
Research Focus
Key Achievements
Top Papers
- 1Nadine Humanoid Social Robotics Platform25 citations · 2019
- 2Uncanny valley for interactive social agents: an experimental study19 citations · 2022
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