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About

Paul Gainer’s research lies at the intersection of formal verification, probabilistic modelling, and human-robot interaction, with a particular focus on ensuring the safety and reliability of autonomous and assistive robotic systems. His work is distinguished by its practical, user-centred approach to verification, addressing critical challenges in how robots can be safely personalised and deployed in dynamic, real-world environments. Gainer’s most-cited paper, "Probabilistic Model Checking of Ant-Based Positionless Swarming" (2016, 11 citations), introduced novel techniques for verifying the emergent behaviours of decentralised swarms, a foundational contribution to the field. He further advanced the state of the art with "CRutoN: Automatic Verification of a Robotic Assistant’s Behaviours" (2017, 10 citations), which demonstrated automated verification for robotic assistants. Notably, his proof-of-concept study (2021, 7 citations) directly addresses the usability of verification methods for detecting behaviour interference when teaching assistive home companion robots, bridging the gap between formal methods and practical, end-user customisation. Through this work, Gainer has made a significant impact on the safe integration of robots into everyday human environments, earning recognition for both technical rigour and real-world applicability.