Profile

Brittany Bogle PhD MPH

IBM Data Science and AI Elite

Contact Details

IBM Data Science and AI Elite

Bio

Dr. Brittany Bogle is a Senior Data Scientist/Machine Learning Engineer with IBM’s Data Science Elite Team. In her current role, she collaborates with clients to design and execute data science use cases. In this role, she has worked with clients across a range of industries, including healthcare, finance, hospitality, and manufacturing. Her expertise in data science spans descriptive analytics, predictive analytics, and decision optimization.

 

Prior to joining IBM, she was a postdoctoral fellow in cardiovascular disease epidemiology at the University of North Carolina at Chapel Hill. During the fellowship, she established and implemented methodology using natural language processing to emulate manual adjudication of myocardial infarction and chronic heart failure within Electronic Healthcare Records (EHR) data, in conjunction with a multi-disciplinary team of epidemiologists, cardiologists, and information systems researchers. Separately, she has built, in collaboration with an emergency medicine physician, a tailorable simulation tool to evaluate EMS routing strategies for suspected endovascular stroke patients. She also developed optimization models to recommend optimal statewide drone station placement with an objective to minimize the time to delivery of Automated External Defibrillators (AEDs) to witnesses of cardiac arrest.

 

Dr. Bogle’s experience in data science also includes using optical character recognition on state birth records to augment lead poisoning risk predictive models for the Chicago Department of Public Health. She collaborated with Northwestern University Department of Preventive Medicine to propose a population-based predictive model for cardiac arrest. She was also a Summer Research Fellow at the RAND Corporation, where she proposed cost-saving optimized inventory policies for military vehicular components and repair. During her PhD, she developed optimization-based methodology for generating completely synthetic data that is able to emulate the statistical properties of real data.

 

Dr. Bogle is the lead author of 8 peer reviewed manuscripts and has presented work at various research conferences including INFORMS, Winter Simulation Conference, American Heart Association and the International Stroke Conference. She holds a Bachelor of Science in Industrial Engineering from the University of Arkansas as well as a MS/PhD in Industrial Engineering and Management Sciences and a Master’s in Public Health from Northwestern University.