Data Science · Clinical Research · Public Health · Future Physician
I build reproducible data science projects focused on healthcare systems, public health, and clinical research.
I'm a senior at Michigan State University (4.00 GPA, Dean’s Research Scholar) studying Data Science and Biotechnology, and I will begin medical school at the University of Toledo College of Medicine and Life Sciences in 2026 through the MedStart program.
My work focuses on using statistical modeling, data pipelines, and clear visualization to study healthcare access, clinical outcomes, and system-level inefficiencies, with growing interest in EMR-based research and real-world clinical data.
| Project | Description | Stack |
|---|---|---|
| MSU Curriculum Maps (Capstone) | Built a reproducible pipeline to transform university curriculum data into prerequisite networks and compute structural metrics (blocking factor, delay factor), enabling data-informed curriculum design and analysis. | Python, Julia, CurricularAnalytics |
| Measles Comeback, Vaccination Gaps and Outbreak Risk | Analyzed CDC, WHO, and Census data to show how vaccination gaps and exemption rates correlate with measles outbreak risk across U.S. states and over time. | Python, pandas, matplotlib |
| Medical Admissions Gap Year Analysis | Investigated AAMC admissions trends to quantify how gap years impact physician workforce timing, introducing a “physician-years” framework to measure systemic delay. | Python, Jupyter, statistical analysis |
| NYC 311 Service Request Analysis | Built an AWS pipeline (S3, Athena, SageMaker) to model complaint resolution time at intake, improving baseline prediction and analyzing service patterns across agencies. | AWS, SQL, Python, scikit-learn |
| Curser | Developed an interactive app that detects phonetic collisions across languages to prevent unintended or offensive naming. Live App | Python, Streamlit, Whisper, NLP |
| Immune Response GWAS FDR Analysis | Compared false discovery rate correction methods in a GWAS, demonstrating how method choice alters SNP-level findings in immune response data. | R, genomics, statistical testing |
- Preparing to begin medical school while building a foundation in clinical and translational data science
- Working toward EMR-based research, including cohort definition, phenotype construction, and outcomes analysis
- Continuing research on medical admissions systems, workforce timing, and healthcare access
- Expanding projects that combine data science with real-world clinical and public health questions
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Undergraduate Research Ambassador, Michigan State University
Advised students on research involvement, led workshops, and supported research accessibility initiatives -
Undergraduate Research Assistant, Hamberger Lab
Plant biotechnology research on regulatory elements for targeted terpene production in sorghum -
Independent Researcher, Cesario Lab
Bayesian modeling of stereotypes using diagnostic ratios, including full project design and statistical analysis -
Medical Assistant, Jagannathan Neurosurgery
Supported patient care, EMR documentation, and clinical workflow in a high-volume neurosurgery practice
