Nati Ofir is a computer vision and remote sensing algorithm researcher with a PhD in Computer Science from Kingston University, London. He is currently working in Prof. Yinon Rudich’s laboratory at the Weizmann Institute of Science, where he specializes in remote sensing, hyperspectral imaging, and AI-driven environmental forecasting. His work bridges academic insight and industrial application, combining deep learning, classical vision techniques, and physics-informed models to solve complex real-world problems.
Nati has a strong track record of scientific contributions, with peer-reviewed publications in top-tier conferences and journals, including CVPR, TPAMI, ICIP, and ICASSP. His research has focused on the challenges of faint edge detection and multispectral image registration, comparing classical and deep learning approaches. In industry, he has held key roles at Applied Materials and Intel’s Imaging and Camera Group, where he developed advanced algorithms for defect detection, stereo depth estimation, and temporal noise reduction. He has a BSc in Computer Science from the Hebrew University, and MSc in Computer Science and Applied Mathematics from the Weizmann Institute of Science, both with honors.