Stanislav Sotnikov

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About

Stanislav Sotnikov is a researcher advancing non-destructive evaluation (NDE) technologies, with a primary focus on Ground Penetrating Radar (GPR) and acoustic inspection methods. His most impactful contribution is the development of GPRNet, a deep learning-based model reconstruction system for detecting and locating underground utilities such as rebars and pipes. This work, published in 2021 with 18 citations, addresses a critical gap: previous methods relied solely on GPR image-based feature detection and could not process sparse GPR measurements. Sotnikov’s approach enables robust 3D reconstruction from limited data, significantly improving the practicality of GPR for civil infrastructure assessment. In related work, he has also tackled wind-turbine blade inspection using an impact-sounding module combined with acoustic analysis, targeting subsurface delamination—a key challenge in renewable energy maintenance. By bridging signal processing, machine learning, and structural health monitoring, Sotnikov’s research offers scalable solutions for both urban utility mapping and wind energy reliability. His work demonstrates a clear trajectory toward automated, data-driven NDE systems that enhance safety and efficiency in critical infrastructure.