Kirill Bronnikov

Russian Academy of Sciences, Novosibirsk State University

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About

Kirill Bronnikov is a leading researcher in the field of fiber optic-based shape sensing, with a primary focus on developing high-precision algorithms for real-time 3D reconstruction. His major contributions center on the characterization and optimization of shape-reconstructing algorithms, particularly comparing transformation matrices against traditional Frenet-Serret equations for multicore optical fibers. In his most cited work (2020, 54 citations), Bronnikov demonstrated how strain evaluation in optical fibers can accurately identify spatial parameters such as curvature radii and bend direction, enabling real-time shape sensing applications. His subsequent research (2020) extended this work by applying transformation matrix algorithms to polyimide-coated 7-core optical fibers, further refining the numerical evaluation of fiber strains for precise 3D shape reconstruction. These contributions are critical for advancing minimally invasive medical procedures, structural health monitoring, and robotics, where accurate, real-time shape sensing is essential. Bronnikov’s work has established him as a key figure in optical fiber sensing technology, with his algorithms providing a robust framework for translating strain data into actionable spatial information.