Papers
28
Total Citations
698
H-Index
13
About
Bahar Irfan is a prominent researcher at the forefront of human-robot interaction (HRI), with a particular focus on socially assistive robotics, long-term personalization, and conversational AI. Her work addresses some of the most pressing challenges in deploying robots in real-world settings, from healthcare to eldercare. Irfan's early contributions tackled the largely overlooked problem of child speech recognition in HRI, a foundational concern for educational and assistive robot applications that has garnered 158 citations. She has also championed the integration of social psychology into HRI research, helping bridge engineering and the behavioral sciences. Her long-term cardiac rehabilitation studies, conducted in clinical settings in Colombia, demonstrated tangible real-world benefits of socially assistive robots, earning significant academic attention with over 60 citations. More recently, Irfan has emerged as a leading voice on companion robots for older adults, critically examining the promises and pitfalls of large language models in open-domain dialogue — work that has rapidly accumulated nearly 80 combined citations. Her research on lifelong learning and personalization further underscores her commitment to robots that adapt meaningfully over time. With over 560 cumulative citations, Irfan's work is shaping how robots can genuinely serve vulnerable populations.
Research Focus
Key Achievements
Top Papers
- 1Child Speech Recognition in Human-Robot Interaction158 citations · 2017
- 2Social Psychology and Human-Robot Interaction80 citations · 2018
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- 4Personalization in Long-Term Human-Robot Interaction58 citations · 2019
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- 6Human-robot sensor interface for cardiac rehabilitation43 citations · 2017
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