Pourya Aliasghari
Papers
10
Total Citations
66
H-Index
4
About
Pourya Aliasghari is a human-robot interaction researcher whose work sits at the intersection of social robotics, robot learning, and trust dynamics. His research primarily investigates how humans perceive, teach, and build trust with trainee robots — machines designed to learn new tasks directly from human instructors. With a body of work accumulating over 60 citations, Aliasghari has made meaningful contributions to understanding how robot errors, nonverbal behaviors, and appearance shape human teachers' confidence in and tolerance of robotic learners. Among his most influential contributions is his exploration of how domestic trainee robots' mistakes affect human trust, garnering 19 citations, alongside complementary work examining how gaze and arm motion kinesics influence a humanoid robot's perceived eagerness and attentiveness. He has also advanced practical methodologies for kinesthetic teaching — physically guiding robots through tasks — studying how non-experts develop teaching proficiency across multiple sessions. More recently, Aliasghari has ventured into biologically inspired imitation learning, proposing novel program-level frameworks drawn from primate behavior to enable robots to acquire complex, sequential skills. Across his portfolio, his research consistently champions the goal of making robots genuinely teachable by everyday people, bridging cognitive science, robotics, and human-centered design.
Research Focus
Key Achievements
Top Papers
- 1Effect of Domestic Trainee Robots’ Errors on Human Teachers’ Trust19 citations · 2021
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- 9A Biologically Inspired Program-Level Imitation Approach for Robots2 citations · 2025
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