Adel Faridani

Papers

Total Citations

H-Index

About

Adel Faridani is a researcher whose work bridges the foundational mathematics of imaging with practical computational systems. His key research areas include computed tomography (CT), inverse problems, and sampling theory, with a particular focus on the theoretical underpinnings of image reconstruction. Faridani is best known for his significant contributions to the analysis of the local tomography problem, where he developed rigorous mathematical frameworks for reconstructing images from limited or truncated projection data—a critical challenge in medical and industrial CT. His work has been highly influential, with his most cited papers amassing hundreds of citations, reflecting their enduring relevance in the field. Notably, his early career included work on a transputer-based vision system for mobile robots, showcasing an ability to apply theoretical insights to real-world hardware. Faridani’s research is distinguished by its clarity and depth, providing essential tools for practitioners in imaging science. His achievements have been recognized through sustained citation impact and his role in advancing the mathematical theory of tomography, making him a key figure for students and researchers exploring inverse problems and signal processing.