Papers
68
Total Citations
820
H-Index
17
About
Mary-Anne Williams is a pioneering researcher at the intersection of human-robot interaction (HRI), social robotics, and artificial intelligence. Her work has fundamentally shaped how we understand the relationship between humans and robots in everyday social contexts, particularly in public and commercial spaces. Williams has made landmark contributions to questions of trust, transparency, and authority in HRI. Her influential 2018 studies — collectively accumulating nearly 200 citations — explored how robot embodiment, preference elicitation, and privacy transparency shape user acceptance and engagement. Notably, her finding that greater transparency fosters user approval has had direct implications for responsible robot deployment in service industries. Her investigation into robot persuasion for food recommendation and the dynamics of robot authority further demonstrate her ability to connect fundamental behavioral questions with real-world applications. Beyond interaction design, Williams has contributed to computational emotion modeling and robot social intelligence, reflecting a broad intellectual range. Her earlier work on case-based gameplay in RoboCup (2004) reveals a long-standing commitment to intelligent autonomous systems. More recently, her research on Fog Robotics addresses the computational infrastructure needed for fluent real-world HRI. With dozens of highly cited publications spanning nearly two decades, Williams stands as a defining voice in shaping socially intelligent, trustworthy robotic systems.
Research Focus
Key Achievements
Top Papers
- 1Design Methodology for the UX of HRI79 citations · 2018
- 2
- 3Be More Transparent and Users Will Like You59 citations · 2018
- 4Computational Emotion Models: A Thematic Review34 citations · 2020
- 5Robot Authority and Human Obedience31 citations · 2017
- 6Bon Appetit! Robot Persuasion for Food Recommendation31 citations · 2018
- 7
- 8Robot Social Intelligence26 citations · 2012
- 9Embodiment, Privacy and Social Robots: May I Remember You?24 citations · 2017
- 10Fog Robotics for Efficient, Fluent and Robust Human-Robot Interaction24 citations · 2018