Etornam Amesimeku is a dedicated professional with a profound commitment to advancing the field of biostatistics in the realm of public health. Etornam holds a Master's degree in Biostatistics from New York University showcasing his unwavering pursuit of academic excellence.
Within the NYU GPH community, he played a pivotal role in the student affairs team, contributing to various activities and initiatives. Notably, he has been recognized as a recipient of the competitive NYU Changemaker Fellowship program through the Wasserman Center. This distinction allowed him to conduct research focused on malaria eradication in Cabo Verde, a demonstration of his commitment to addressing critical global health challenges. In various projects and leadership capacities, he has showcased his analytical skills, collaborating on research related to COVID-19 and geriatric care in both the ISEE Lab and NYU Biostatistics Consulting Lab.
Currently, he serves as a Course Assistant for the Categorical Data Analysis, where he diligently holds office hours to provide valuable guidance and support to fellow students. In this role, he also plays a crucial role in evaluating assignments. His passion lies in applying advanced statistical methods to address pressing health-related issues. His research interests span a wide spectrum, encompassing areas such as cancer, cardiovascular diseases, HIV/AIDS, and malaria. His overarching career goal is to become a seasoned biostatistician, dedicated to bolstering the global health system through rigorous and impactful research.
Currently, he is engaged in a challenging and impactful project at NYU Langone Internal Medicine through NYU Biostatistics Consulting Lab. Specifically, he is leading a comprehensive analysis using statistical methods and machine learning techniques to predict donor discard in lung organ transplantation. This project relies on extensive data sourced from the United Network for Organ Sharing (UNOS) database, providing valuable insights into organ transplantation practices. His role in this endeavor involves applying advanced statistical methodologies to evaluate factors affecting the decision to discard donor lungs. By harnessing machine learning algorithms, He aims to develop predictive models that can enhance decision-making processes regarding lung organ transplantation. This project holds significant potential for improving organ utilization, ultimately increasing the chances of successful lung transplants.
Beyond his professional commitments, Etornam indulges in interests such as soccer, table tennis, music, travel, and poetry writing. With his exceptional education and hands-on experience in biostatistics, he stands poised to make an indelible mark in the sphere of global public health.
I believe that knowledge ceases to be power if it is not shared. Hence, I chose to become a mentor within the SGPHF program, enabling me to disseminate the insights I have gained from my experiences at the ISEE lab to both fellow lab members and a broader audience.