Alexander Zelensky

Lomonosov Moscow State University, Research and Production Complex Technological Centre

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About

Alexander Zelensky is a researcher at the forefront of integrating deep learning with manufacturing and augmented reality. His work focuses on two key areas: enhancing depth map quality for robotic systems and enabling real-time semantic segmentation for 3-D augmented reality. In his 2023 study on defect detection, Zelensky developed a deep learning system to remove depth map noise caused by material fragments during robotic tasks like welding and milling. This innovation improves object tracking and 3-D reconstruction, directly boosting precision in automated manufacturing. His second major contribution, also from 2023, tackles the challenge of real-time foreground extraction on limited hardware, such as smartphones, for augmented reality applications. By optimizing deep learning semantic segmentation, he makes AR more responsive and practical for dynamic environments. Though his most-cited papers currently have 2 citations each, they represent foundational steps in bridging AI with industrial and visual technologies. Zelensky’s work is notable for its practical focus on real-world constraints—from factory floor debris to mobile processing limits—positioning him as an emerging voice in applied computer vision and robotics.