Jaejin Cho

Jaejin Cho is an Assistant Professor in the Department of Artificial Intelligence and Robotics at Sejong University, where he conducts research at the intersection of machine learning and medical imaging. His work primarily focuses on advancing Magnetic Resonance Imaging (MRI) techniques through computational methods.

His research interests span several key areas:

• Machine Learning: Network design, Domain transform, and Manifold learning.
• Image Processing: Numerical optimization, Annihilating filter, and Low-rank reconstruction.
• Medical Imaging: Fast MRI acquisition, Physics modeling, and MRI scanner operation.

Dr. Cho's recent publications reveal a consistent focus on developing deep learning-based reconstruction algorithms for accelerated and distortion-free MRI. His work often integrates model-based approaches with deep learning, emphasizing zero-shot and self-supervised learning to avoid the need for large training datasets. Key application areas include quantitative MRI, diffusion imaging, and multi-contrast mapping, with a strong emphasis on clinical translation and cross-platform reproducibility.

No scientific awards were mentioned in the available information.

No information was available regarding advising activities, grants, or laboratory teams beyond his GitHub repositories which include tools for MRI reconstruction such as wave-modl and wave-qalas.