I am interested in applying data science and machine learning techniques to analyzing electronic health record (EHR) data to improve clinical care and administrative operations. Applications range from quality monitoring and dashboard creation, to machine learning models for clinical decision support. 

Projects topics have ranged from nursery census and unit closure tracking; readmission tracking and reduction; unintended extubation reduction; admission / problem list and morbidity & mortality report generation; reducing newborn hypothermia on admission; optimizing management of neonatal abstinence syndrome; hearing screen and CMV screening for divisional quality improvement; reducing time to first enteral feed; impact of infant cue-based feeding; optimizing growth and nutrition tracking; central line utilization; analyzing nursing primary care team composition; NICU family meeting tracking; Pasteurized human donor milk utilization tracking; hyperbilirubinemia clinical decision support and predictive modeling; and natural language processing of clinical notes for newborn outcome prediction.