معرفی
Dr. Daniel Pak is a Research Fellow in the Department of Radiology & Biomedical Imaging at Yale School of Medicine, Yale University. His research focuses on advancing medical imaging techniques through deep learning and computational methods, with a particular emphasis on cardiovascular biomechanics, MRI reconstruction, and automated meshing for personalized medicine. He also explores the environmental and public health impacts of synthetic chemicals, particularly their causal links to mitochondrial dysfunction and diabetes.
His work integrates interdisciplinary approaches, combining machine learning with biomedical engineering to address challenges in medical diagnostics and treatment planning. Notable contributions include developing AI-driven tools for multimodal modeling of aortic stenosis and robust automated calcification meshing. He has also contributed to cross-modality segmentation frameworks and data-driven heart geometry modeling.
While no formal advisees are listed, his research collaborations span diverse fields. His publications highlight a commitment to translational research, bridging theoretical advancements with clinical applications. Awards and grants are not explicitly mentioned in the provided materials.
