Yujia Liu

About

Yujia Liu is a leading researcher in human-robot interaction, specializing in the design and communication strategies of in-vehicle robots and anthropomorphic agents. Her work focuses on how robots can effectively express emotions, provide transparent information, and ensure safety through multimodal warnings. Liu’s major contributions include demonstrating that robot transparency and anthropomorphic attributes significantly enhance human-robot performance and user experience, as shown in her 2021 study (18 citations). She has pioneered the application of transparency theory to proactive in-vehicle robot interactions (2022, 11 citations) and explored abstract emotional expression in robot faces (2021, 13 citations). Her research on multimodal warnings for driving safety scenarios (2022, 10 citations) addresses critical safety challenges, while her latest work investigates user preferences for anthropomorphic virtual robots in augmented reality head-up displays (2023). With a growing citation impact, Liu’s work bridges engineering, psychology, and design, offering practical insights for developing safer, more intuitive automotive agents. Her studies are essential reading for anyone interested in the future of human-vehicle interaction and emotionally intelligent robotics.

Research Focus

Key Achievements

Top Papers

1. 1
   Robot Transparency and Anthropomorphic Attribute Effects on Human–Robot Interactions

   18 citations · 2021
2. 2
   Experimental Study on Abstract Expression of Human-Robot Emotional Communication

   13 citations · 2021
3. 3
   Design of Proactive Interaction for In-Vehicle Robots Based on Transparency

   11 citations · 2022
4. 4
   Multimodal Warnings Design for In-Vehicle Robots under Driving Safety Scenarios

   10 citations · 2022
5. 5
   Investigating User Preferences for In-Vehicle Virtual Robots’ Anthropomorphic Appearance in Augmented Reality Head-Up Display

   2 citations · 2023

Key Collaborators

Contact & Links