Jing Qin

Jing Qin is an Associate Professor in the Department of Mathematics at the University of Kentucky, within the College of Arts & Sciences. His research focuses on Mathematical Optimization, Variational Image Processing, Compressive Sensing, and computational analysis of imaging data. His work addresses challenges in signal recovery, tensor decomposition, hyperspectral imaging, and machine learning applications.

Recent publications emphasize advancements in tensor recovery algorithms, hyperspectral band selection, and graph-based signal processing. These contributions highlight innovations in iterative methods, regularization techniques, and deep learning models for structural analysis and robotic systems. Qin’s research bridges theoretical optimization frameworks with practical applications in remote sensing, medical imaging, and computer vision.

His articles reflect a strong focus on interdisciplinary solutions, combining mathematical rigor with computational efficiency. Despite no explicitly listed awards or grants, his prolific publication record underscores sustained scholarly impact. Further details are available via his faculty webpage: http://ms.uky.edu/~jqi229/.