Charles Delahunt
Seattle, Washington, United States
Summary
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SeniorCharles Delahunt is a Senior Research Engineer on the ML team at Global Health Labs, where he shapes end-to-end machine learning solutions—from data collection and cleaning to deployment—driven by concrete global health use cases in low-resource settings. He leads projects in detection of neglected tropical diseases (Loa loa, S. haematobium) and pregnancy risk prediction, with a track record including automated malaria diagnosis, grain moisture forecasting for smallholders, and lung ultrasound analysis. His work emphasizes translating medical needs into tailored ML algorithms, and he actively cultivates the global health ML community through conference workshops and service on ASTMH’s schistosomiasis sub-committee and the RISE-MICCAI board. He combines biology-inspired neural networks that learn from very small datasets with data-driven equation discovery approaches, linking UW research on noisy data and biological toolkits to practical ML. His background spans an MIT mathematics degree, a PhD in Electrical Engineering and Applied Math from the University of Washington, and a postdoc in ML, reflecting a strong foundation in theory and real-world impact. Based in Seattle, he also maintains a GitHub presence focused on porting biological learning mechanisms to ML and applying ML to global health challenges like malaria.
10 years of coding experience
Github Skills (6)
mnist9
deep-learning5
machine-learning5
incremental-learning5
python4
neural-network3
Programming languages (2)
Github contributions (5)
charlesDelahunt/PuttingABugInML
Jan 2018 - Jun 2019
Code for the paper "Putting a bug in ML: The moth olfactory network learns to read MNIST", by CB Delahunt and JN Kutz
Contributions:13 commits, 1 PR, 7 pushes in 1 year 4 months
deep-learningneural-networksmachine-learningincremental-learningneural-network
charlesDelahunt/SmartAsABug
Jan 2018 - Apr 2019
Contributions:12 commits, 8 pushes, 1 branch in 1 year 3 months
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