Alireza Ahmadi
Papers
3
Total Citations
24
H-Index
2
About
Alireza Ahmadi is a robotics researcher whose work focuses on human-robot interaction, specifically enabling robots to perceive, track, and socially engage with people in natural settings. His key research areas include skeleton and visual tracking fusion, adaptive social behaviors, and attention control for mobile service robots. In his most cited work (2015, 12 citations), Ahmadi developed a novel method combining skeleton and visual tracking to overcome the limitations of depth-based skeleton trackers, successfully implementing it on his service robot, Sepanta, for human-following tasks. His second major contribution (2014, 10 citations) introduced an adaptive handshaking system where robots adjust their behavior based on gender detection and person recognition, allowing for personalized interactions that change with familiarity. Ahmadi also explored top-down attention control models (2015, 2 citations) to reduce sensory data complexity on omnidirectional mobile platforms. His work bridges computer vision, social robotics, and cognitive architectures, demonstrating how robots can both track humans reliably and engage them with socially appropriate physical gestures. With cumulative citations across these foundational papers, Ahmadi’s research provides practical frameworks for service robots that must navigate and interact with people in dynamic, real-world environments.
Research Focus
Key Achievements
Top Papers
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