Charles Delahunt has over 10 years’ experience applying ML to global health challenges including malaria diagnosis, neglected tropical disease diagnosis, ultrasound (lung and obstetric), and intrapartum monitoring. He also held a postdoc researching ML methods at University of Washington’s applied math department. He serves on the scientific committee of the American Society of Tropical Medicine and Hygiene; has advised the WHO on digital microscopy for malaria; has organized multiple conference workshops and given invited talks on ML for global health; and serves on the board of RISE-MICCAI. His work focuses on understanding the requirements of the clinical use-case and building these requirements into the structure of ML solutions at every stage of ML development (e.g. as architecture choices, evaluation metrics, loss functions, and biophysical priors).