Surapa Thiemjarus

Imperial College London, Thammasat University

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About

Dr. Surapa Thiemjarus is a leading researcher in medical robotics and human-robot interaction, with a focus on probabilistic modeling for real-world sensing challenges. Her most influential work, "A Probabilistic Framework for Tracking Deformable Soft Tissue in Minimally Invasive Surgery" (2007, 53 citations), introduced a novel Bayesian approach to address the critical problem of tracking soft, non-rigid tissues during surgical procedures—a key enabler for safer, more precise robotic-assisted surgery. This contribution has been widely recognized for advancing computer-assisted intervention. In parallel, Dr. Thiemjarus has explored intelligent human-robot collaboration, as demonstrated in her work on a "Speaker tracking module for indoor robot navigation" (2012, 3 citations). This study proposed a Bayesian sound source localization method using time delay of arrival (TDOA) features, enabling mobile service robots to autonomously navigate toward a human speaker in response to voice commands. By bridging probabilistic inference with practical robotics, Dr. Thiemjarus has made notable contributions to both surgical robotics and intuitive human-robot interfaces, laying groundwork for more adaptive and responsive autonomous systems.