Public Health ePortfolio

About Me

I am an MPH student passionate about translating data into action. With training in epidemiology, disease surveillance and molecular biology, I combine analytical rigour with hands‑on experience to support infectious disease research and public health interventions. My work spans vector‑borne disease prevention, chronic disease analytics and health equity mapping. I thrive on collaboration and bring a systems‑thinking approach to complex health challenges.

Education

Master of Public Health, University of Georgia (GPA 4.00, expected Aug 2026) – Coursework includes public health surveillance, biostatistics, health policy & management, environmental health science and disaster management.
Bachelor of Science in Biological Sciences (Neurobiology), Georgia State University (GPA 3.64, May 2024) – Completed rigorous coursework in genetics, cell & molecular biology, microbiology & public health and clinical neuroscience.

Skills

Analytical & Technical

Communicable disease surveillance, case investigation and contact tracing
Data wrangling and statistical analysis (Python, R, SAS)
Interactive dashboarding (Tableau, Power BI) and GIS mapping
Machine learning & time‑series forecasting for health data
EHR/claims data exploration and SQL querying

Soft & Leadership

Effective communication & health education
Team collaboration and project management
Program planning & evaluation using CDC frameworks
Cultural competence & community engagement
HIPAA compliance and data privacy best practices

Projects

Chronic Disease Trend Analysis

Analyzed 20 years of obesity and diabetes prevalence across U.S. states using CDC BRFSS data. Built interactive line charts and choropleth maps to highlight geographic disparities and trends over time.

Behavioral Risk Factor Modeling

Used BRFSS survey data and SAS to identify lifestyle factors associated with hypertension. Applied survey weights, ran multivariable logistic regression and interpreted odds ratios to inform public health messaging.

Heart Disease Risk Prediction

Developed a suite of machine learning models (logistic regression, random forest, XGBoost) on UCI heart disease data to predict presence of heart disease. Evaluated models with ROC‑AUC and explained feature importance to health audiences.

Geospatial Health Mapping

Created an interactive map of diabetes prevalence and healthcare facility locations at the county level using Python (GeoPandas/Folium). Identified clusters of high burden and poor access to inform resource allocation.

EHR Data Exploration

Performed exploratory analysis on synthetic ICU data (MIMIC‑IV). Queried patient demographics and diagnoses via SQL, summarized length of stay and visualized top admission reasons using Python.

NLP on Clinical Text

Applied NLP techniques to de‑identified clinical notes to extract symptom and medication entities using spaCy and BioBERT. Generated word clouds and identified common themes in discharge summaries.

Contact

If you’d like to collaborate or learn more about my work, please get in touch: