Papers

6

Total Citations

59

H-Index

3

About

Nicola Webb is a researcher specializing in social robotics, human-robot interaction, and affective computing, with a particular focus on enabling robots to perceive and respond to human social cues. Her foundational work in facial expression recognition established deep learning frameworks capable of operating in real-time and unconstrained environments — a technically demanding challenge given the sensitivity of neural networks to shifts in data distribution. Her 2018 and 2020 papers on this topic have collectively garnered over 40 citations, underscoring their significance to the field. Webb's research has since expanded to encompass broader dimensions of social awareness, developing novel metrics for measuring visual social engagement through proxemics and gaze analysis — work she has refined and validated in real-world settings across multiple publications. More recently, her investigations into human-robot teaming have tackled the critical question of trust, examining how swift trust forms in mobile ad hoc teams and how co-movement dynamics shape ongoing trust development. Together, these contributions trace a coherent and ambitious research trajectory: building socially intelligent robots that can read human intentions, integrate seamlessly into teams, and earn the trust necessary to operate effectively alongside people in high-stakes environments.

Research Focus

Key Achievements

3
H-Index
6
Papers
59
Total Citations
10
Avg Citations/Paper
🏆 Most Cited Paper
Deep Learning for Real Time Facial Expression Recognition in Social Robots
23 citations · 2018
📈 Most Prolific Year: 2024 (2 Papers)
🤝 Key Collaborators: 14
🏛 Institutions: Coventry University, University of the West of England, University of Bristol, University of Birmingham

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
Content generated · 13 days ago