Cigdem Turan
Papers
2
Total Citations
25
H-Index
2
About
Dr. Cigdem Turan is a pioneering researcher at the intersection of social robotics and interactive machine learning. Her work focuses on two critical challenges: enabling robots to generate authentic, dynamic facial expressions and developing robust systems for learning from human feedback. In her highly cited 2022 paper, "ExGenNet," Dr. Turan introduced a novel framework that uses facial expression recognition to automatically generate robotic expressions, moving beyond rigid, preprogrammed configurations. This work, garnering 21 citations, directly enhances robot sociability in human-robot interaction. Complementing this, her research on Interactive Reinforcement Learning (IRL) tackles the practical problem of unreliable human advice. In her 2022 paper on the subject, she developed methods to allow robots to learn effectively even when human action suggestions are imperfect, a crucial step for deploying robots in real-world, noisy environments. By bridging the gap between expressive, socially-aware robots and resilient learning algorithms, Dr. Turan is laying the groundwork for more intuitive and trustworthy autonomous systems.
Research Focus
Key Achievements
Top Papers
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