Kim Lindberg Schwaner
Papers
7
Total Citations
95
H-Index
5
About
Kim Lindberg Schwaner is a robotics and biomedical engineering researcher whose work sits at the intersection of autonomous surgical robotics, learning from demonstration, and bioimpedance-based tissue sensing. Schwaner's most impactful contributions focus on enabling surgical robots to perform complex tasks independently, most notably through frameworks that allow robots to learn surgical action primitives from a single human demonstration. His 2021 papers on autonomous needle manipulation and bi-manual surgical suturing — garnering 32 and 17 citations respectively — demonstrated that robots could execute complete suturing sequences, including needle pick-up, insertion, re-grasping, and hand-over, without continuous human guidance. Equally significant is Schwaner's pioneering development of robot-assisted electrical bioimpedance scanning (RAEIS) systems, designed to detect critical subsurface structures such as lymph nodes during minimally invasive surgery — a challenge made harder by the absence of haptic feedback in robotic systems. This line of work, spanning from a 2019 feasibility study to active lymph node search algorithms by 2022, has accumulated over 40 citations and addresses a genuine clinical safety need. His earlier work on improving surgical robot precision through cascade control further underscores his commitment to making autonomous robotic surgery reliable and clinically viable.
Research Focus
Key Achievements
Top Papers
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