Samuel Wong

Samuel Wong is a Visiting Professor in the Physics Department at Stanford University, affiliated with the School of Humanities and Sciences. His research focuses on radiomics, machine learning applications in pediatric neuro-oncology, and medical imaging diagnostics. He has contributed to multinational studies on posterior fossa tumors and neonatal critical care protocols. Notably, he developed radiomic phenotyping techniques to differentiate pediatric brain tumors like ATRT from medulloblastoma. His work bridges computational methods with clinical practice, emphasizing translational medicine.

Recent publications (2021-2022) highlight advancements in diagnostic algorithms for pediatric tumors, neonatal transport intubation protocols, and cardiorespiratory management of extremely preterm infants. A 2012 paper explored historical financial market structures at the NYSE. His collaborations span institutions globally, reflecting a commitment to interdisciplinary research.

No specific awards or grants are listed, though his involvement in high-impact clinical studies suggests recognition in medical physics and oncology domains. He advises no listed students but collaborates with research teams in physics and biomedical engineering laboratories at Stanford.