Leads development, validation, and deployment of machine-learning pipelines for high-dimensional spectral flow-cytometry data and measurable residual disease detection. The work covers clustering, dimensionality reduction, classification, anomaly detection, predictive modeling, drift monitoring, reproducible workflows, and clinically validated diagnostic analytics.
Data Scientist - Clinical Machine Learning & Flow Cytometry
St. Jude Children's Research Hospital