PhD in MRI with expertise in advanced pulse sequence design, iterative MRI reconstruction, and high-performance computing. My current research at the Martinos Center focuses on field shimming, SAR management, and MR sequence design. I develop GPU-accelerated algorithms and motion-compensated reconstruction methods to advance clinical MRI applications.
This thesis addresses motion-compensated MRI reconstruction at ultra-high field (7T). The GRICS method was profiled and implemented on GPU using CUDA, achieving up to 14× acceleration on NVIDIA A100. Pseudo-randomized k-space trajectories were designed for MPRAGE & MP2RAGE sequences to distribute motion effects uniformly. Rigid and non-rigid motion models were compared, and the GRICS approach was benchmarked against a deep learning method (MC-NET), demonstrating superior sharpness and robustness for in vivo brain imaging at 7T.
Instructor for Bachelor students covering mathematical analysis, functions, and the physics of Magnetic Resonance Imaging.
Instructor for Bachelor students in mathematical analysis, functions, geometry, and MRI physics fundamentals.