Pooja Prajod
Papers
11
Total Citations
73
H-Index
6
About
Pooja Prajod is a leading researcher at the intersection of human-robot collaboration (HRC), affective computing, and socially interactive robotics. Her work focuses on making industrial robots more responsive and adaptive to human emotional and cognitive states, with a particular emphasis on understanding neurodiversity in collaborative settings. Prajod’s most cited paper (14 citations) investigates behavioral patterns in robotic assembly tasks, comparing neurotypical and Autism Spectrum Disorder participants—a pioneering step toward inclusive HRC. She has made major contributions to gaze-based attention recognition (13 citations), demonstrating how natural social cues like eye contact can initiate more fluid human-robot interactions. Her research on “Flow” state detection (7 citations) uses multimodal analysis to optimize perceived challenge in industrial scenarios, while her recent work on socially interactive agents (5 citations) extends these principles to robotic neurorehabilitation training. Prajod has also developed a parametric humanoid emotion model (3 citations) and explored the Pleasure-Arousal-Dominance (PAD) framework for emotional co-regulation (6 citations). With over 70 total citations across her publications, Prajod is shaping the future of empathetic, socially aware industrial robotics—bridging the gap between technical performance and human well-being.
Research Focus
Key Achievements
Top Papers
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- 2Gaze-based Attention Recognition for Human-Robot Collaboration13 citations · 2023
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- 9On the Expressivity of a Parametric Humanoid Emotion Model3 citations · 2020
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