Papers
27
Total Citations
691
H-Index
12
About
X. Jessie Yang is a leading researcher in human-robot interaction and human factors engineering, with a particular focus on the dynamics of trust between humans and autonomous systems. Her work has fundamentally reshaped how the field conceptualizes trust in automation — moving beyond static, snapshot measurements to model trust as an evolving, dynamic process. Her 2017 study on user experience and system transparency (195 citations) established foundational insights into how trust develops over time, while her 2020 Bayesian inference framework (125 citations) introduced rigorous computational tools for predicting trust fluctuations in human-robot teams. Yang has extended this work into high-stakes real-world settings, examining how clinical professionals calibrate trust in robotic decision support systems within hospital environments. Her more recent contributions explore trust-aware robot planning, reverse psychology strategies in human-robot interaction, and personalized value alignment — demonstrating a sophisticated understanding of how robots can actively shape collaborative outcomes. Her 2024 TIP model advances the field further by scaling trust modeling to complex multi-human, multi-robot teams. Collectively, Yang's body of work, exceeding 500 citations, has made her an influential voice in designing safer, more transparent, and more effective human-autonomy partnerships.
Research Focus
Key Achievements
Top Papers
- 1
- 2
- 3Robotic assistance in the coordination of patient care73 citations · 2018
- 4Clustering Trust Dynamics in a Human-Robot Sequential Decision-Making Task41 citations · 2022
- 5Reverse Psychology in Trust-Aware Human-Robot Interaction32 citations · 2021
- 6
- 7Robotic Assistance in Coordination of Patient Care27 citations · 2016
- 8
- 9
- 10