Prasad Theeda

Prasad Theeda is a Research Fellow at the Malaysia School of Information Technology, specializing in signal processing, medical imaging, and computational mathematics. His work focuses on compressed sensing, tomographic reconstruction, and optimization techniques applied to imaging systems. He has contributed to advancements in minimizing radiation exposure in CT scans through preconditioned sensing matrices and sparse-view algorithms.

• Key research areas: Compressed sensing, frame theory, medical imaging optimization

His publications span topics like sparse sampling strategies for X-ray tomography and nullspace property analysis in invertible operators. Collaborations include work with institutions on global optimization and inverse problems.

No formal awards or grants are listed, though his research demonstrates significant technical contributions to imaging science.