Sinem Kuz
Papers
18
Total Citations
197
H-Index
9
About
Sinem Kuz is a pioneering researcher at the intersection of cognitive science and industrial robotics, whose work fundamentally explores how humans perceive and collaborate with robotic systems. Her primary research areas include human-robot interaction, anthropomorphism in industrial automation, and cognitive engineering of assembly processes. Kuz’s major contribution lies in demonstrating that endowing industrial robots with anthropomorphic—or human-like—movements and behaviors can significantly improve human acceptance, trust, and comfort in collaborative settings. Her most-cited paper (27 citations) investigates gender effects in observing robotic actions, revealing nuanced perceptual differences that impact co-working dynamics. Across her body of work, which has garnered over 160 citations, Kuz has systematically shown that mimicking human motion profiles and mirror neuron activation can reduce mental workload and enhance safety in assembly cells. Notably, her two-part study on using anthropomorphism to improve human-machine interaction (over 35 combined citations) provides a foundational framework for designing more intuitive industrial robots. By bridging cognitive modeling with practical automation, Kuz has established herself as a key voice in making industrial robots not just efficient, but genuinely collaborative partners.
Research Focus
Key Achievements
Top Papers
- 1Gender Effects in Observation of Robotic and Humanoid Actions27 citations · 2020
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- 4Towards Anthropomorphic Movements for Industrial Robots17 citations · 2013
- 5Mirror Neuronsand Human-robot Interaction in Assembly Cells16 citations · 2015
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- 8Cognitive Engineering of Automated Assembly Processes12 citations · 2011
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