Ihunna Amugo

Provided trauma-informed crisis counseling for 300+ high-acuity cases and delivered QA feedback that reduced documentation errors by 40%.

Selected for an NIH-funded traineeship to query and model 350K+ de-identified EHRs from the N3C Data Enclave to study cardiovascular mortality by race, sex, and vaccine type; built predictive models and delivered Streamlit dashboards and reproducible GitHub/Jupyter workflows.

Developed a Medicare readmission risk classifier, a CNN for oral lesion detection, and an NLP topic modeler; deployed projects on Google Cloud while collaborating in Git-based teams.

Maintained dental EHRs (Epic, Axium) for 85+ patients/day and streamlined ICD-10 coding, SOAP notes, and patient portal workflows to improve clinical documentation efficiency.

Managed 26K+ case investigations for COVID-19, STIs, and monkeypox and automated surveillance workflows in R and SQL, reducing reporting lag by 75%.

Completed an intensive clinical research training certificate focusing on clinical trial design, biostatistics, and regulatory science applied to clinical and AI research.

Completed an AI/ML certificate program emphasizing applied machine learning projects including CNNs and NLP for health domains.

Activities and societies: Core coursework and projects involving EHR systems, data analytics, and health policy.

Completed dual graduate programs in Health Administration and Health Informatics with coursework in healthcare law, biostatistics, health informatics, project management, data analytics, health policy, and EHR systems.

Earned dual Bachelor of Science degrees in Biology and Interdisciplinary Health Services with foundational coursework supporting public health and biomedical research.

Activities and societies: Undergraduate research and public health–related coursework.

Earned Bachelor of Science degrees in Biology and Interdisciplinary Health Services with foundational training relevant to public health and research.