Current area of practice:

Machine learning for global health. In particular, closely tailoring ML solutions to the specific needs of the medical use case.

Work:

(2013 - current) Senior research scientist at Global Health Labs, Bellevue, WA.

Our team develops machine learning algorithms to address health care needs in low-resource settings. Projects include:

• Automated diagnosis of malaria using microscopy images of blood films

• Diagnosis of Neglected Tropical Diseases (eg Loa loa, schistosomiasis)

• Assessing vitamin A deficiency via pupillary response videos

• Predicting moisture content of drying grain (very low-cost device)

• Ultrasound diagnosis of lung conditions

• Obstetric ultrasound

• Cervical cancer detection

• Pregnancy risk stratification

(2013 - 2021) University of Washington, Seattle, WA: PhD in Electrical Engineering; Swartz Foundation Scholarship in neuroscience; Research Postdoc in Applied Math, PI J. Nathan Kutz

Projects included:

• Understanding biological learning mechanisms and porting them to neural nets.

• Use of ML to deduce governing equations of physical systems from noisy experimental data.