Matthew Lewis
Papers
24
Total Citations
543
H-Index
11
About
Matthew Lewis is a researcher at the intersection of social robotics, affective computing, and human-robot interaction, with a particular focus on how autonomous robots can meaningfully engage with vulnerable human populations. His most influential work emerged from the ALIZ-E project, which examined long-term adaptive social interaction between children and humanoid robots, earning over 200 citations and establishing foundational principles for multimodal child-robot engagement. Lewis has made notable contributions to therapeutic robotics, most prominently through Robin — an affective robot toddler designed with simulated diabetes to support self-efficacy and emotional wellbeing in diabetic children, reflecting a deeply human-centered design philosophy. His research extends into the cognitive and motivational architectures underpinning robot behavior, including hedonic decision-making, arousal regulation, and hormone-driven epigenetic adaptation mechanisms that allow robots to respond dynamically to their environments. More recently, Lewis has ventured into computational psychiatry, developing robot models of obsessive-compulsive spectrum disorders to advance understanding of embodied mental health phenomena. His early work on common HRI metrics also helped shape evaluation standards across the field. Collectively, his portfolio demonstrates a sustained commitment to building robots that are not merely functional, but genuinely socially and emotionally intelligent.
Research Focus
Key Achievements
Top Papers
- 1Multimodal Child-Robot Interaction: Building Social Bonds206 citations · 2013
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- 3Children's adaptation in multi-session interaction with a humanoid robot46 citations · 2012
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- 5Common metrics for human-robot interaction32 citations · 2004
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- 7A Hormone-Driven Epigenetic Mechanism for Adaptation in Autonomous Robots25 citations · 2017
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