Clément Mugenzi

I am an ambitious and dynamic scientist with a Master of Science degree in Biostatistics from Columbia University Mailman School of Public Health.

During my undergraduate education in Chemistry at the University of Central Arkansas, I served in different professional and research roles. As a result, I have a wide range of experience working at academic institutions, research labs, as well as small and large companies.

During the summer of 2020, I was privileged to work with Andrew Laine, PhD and Elsa Angelini, PhD in their research lab: Heffner Biomedical Imaging Lab. My goal in this research was to analyze segmented Computed Tomography (CT) images from COPD patients to:

• Create informative visualization plots showing transitions of emphysema subtypes from baseline to follow up.

• Quantify the amount of emphysema pixels present and study the association of emphysema subtypes from baseline to follow up using a Logistic regression model.

• Use supervised learning methods such as Multivariate Adaptive Regression Splines (MARS) and Extreme Gradient Boosting (XGBoost) models to predict the percentage emphysema pixels we would expect at follow up.

Currently, I am part of the wider Analytics & Behavior Change team at CVS health where I am building predictive models to identify Medicaid members most at risk of adverse events such as high healthcare costs, emergency visits, and inpatient admissions.

I am also leveraging Causal Inference and statistical learning methodologies to measure the effectiveness of care management programs and communicate findings to stakeholders for program improvement through better member targeting.

Side Note:

I am a proactive learner, always seeking out challenging opportunities with an ultimate purpose to grow personally and professionally.

I am a data scientist, constantly looking to get involved in challenging projects in order to apply my analytical and problem-solving skills and translate big picture ideas into tangible goals.

Do not hesitate to reach out via email or cell phone for possible collaboration on machine learning projects or Data Science opportunities.