Daniel Yoo is a postdoctoral researcher with expertise in Biostatistics and Development of virtual biopsy systems for the automation of kidney transplantation diagnosis. He completed his PhD at Université Paris Cité, focusing on machine learning applications in health-related fields. His research interests include Machine Learning, Data Science, Public Health, and Epidemiology, particularly in projects aimed at addressing the UN Sustainable Development Goals. Yoo is involved in significant active projects, among them the MALOBIC project, which aims to identify obesity causes in children using machine learning techniques. He actively collaborates with doctoral students and participates in various academic activities, including peer reviewing manuscripts and presenting at conferences. His contributions extend beyond research; he serves as a member of the Danish Data Science Academy and engages in community awareness regarding sustainable health practices.
Danmarks Tekniske Universitet • Kgs. Lyngby, Denmark
Conducting research in Biostatistics and developing projects related to machine learning in healthcare.