Hamid Abrishami Moghaddam

Université de Picardie Jules Verne, K.N.Toosi University of Technology

Papers

Total Citations

H-Index

About

Hamid Abrishami Moghaddam’s research bridges biomedical optics and adaptive machine learning, with a focus on near-infrared spectroscopy (NIRS) and face recognition. His most cited work, “Experimental investigation of NIRS spatial sensitivity” (2011, 57 citations), tackles a critical challenge in medical diagnostics: pinpointing the origin of NIRS signals to improve clinical interpretation of hemodynamic changes. This contribution addresses long-standing uncertainties that have limited NIRS’s adoption in real-world medical settings. In parallel, Moghaddam has advanced adaptive feature extraction for computer vision. His 2007 papers on “Adaptive Modified PCA” and “A New Incremental Face Recognition System” (each with 4 citations) introduced algorithms that combine Sanger’s adaptive PCA and incremental LDA, enabling real-time facial recognition in dynamic environments like mobile robotics. These works emphasize practical, online learning—a departure from static batch methods. While his citation counts are modest, Moghaddam’s research demonstrates a clear trajectory: from foundational NIRS sensitivity analysis to adaptive systems for autonomous applications. His work is particularly relevant for students exploring how signal processing and machine learning converge in both healthcare and robotics, offering a blueprint for tackling real-world constraints like data streaming and sensor uncertainty.