• Awarded one of 10 Cordeiro Summer Research Fellowships for outstanding independent research related to health. • Analyzed data from over 3 million Medicare beneficiaries, identified quantitative associations between heat exposure and hospitalization costs, and applied novel statistical methods to investigate effect modification by race, income, and green space access. • Presented findings to department faculty and senior research collaborators at weekly working group meetings. • Wrote and submitted research proposals and project reports to continually earn funding from competitive sources. Selected as term-time and summer Harvard College Research Program fellow.

Led team in developing strategies for a major professional sports team to increase annual profits. Built detailed financial models and conducted in-depth company and industry research to generate innovative solutions. Presented key findings and actionable research-based recommendations to clients using PowerPoint deliverables.

Collaborated with 5-person team to analyze large datasets using Microsoft Excel and specialized software for a T5 global healthcare company. Created informative metrics to guide clinical trial design and optimize patient experiences.

Led research teams throughout development of projects analyzing and visualizing Harvard data. Directed outreach initiatives to collect data for project use. Wrote and edited research articles for publication on organizational website.

Selected among 20 out of 400+ applicants to receive full scholarship to NIH biostatistics institute. Analyzed data from 30,000+ CDC survey respondents, identified significant risk factors of osteoporosis, and developed risk model using R and SAS statistical software in collaborative research project. Presented findings to program faculty.

Conducted computational analysis of genetic and environmental data from 500,000+ UK Biobank participants. Built functions and wrote code in Python to determine relationships between gene mutations and disease phenotypes. Developed statistical models to predict disease risk.

Analyzed biological literature and collected data used to develop mathematical models for SARS-CoV-2 replication in order to identify potential antivirals. Collaborated with team of undergraduate and graduate students led by professor of chemical and biomolecular engineering. Improved understanding of coronavirus molecular virology, biological laboratory techniques, and applications of computing and mathematics to biological processes.