A master student in the Biostatistics program at Duke University with a solid education in quantitative data analysis.
Two years of research experience in biomedical EHR research.
Good at using SAS, R, and Python programming in cleaning, manipulating, analyzing, and visualizing big data.
A good team player and a quick learner with excellent communication, problem-solving, and multi-tasking skills.
Overview
3
3
years of professional experience
Work History
Research Assistant
Chuan Hong
Durham, NC
04.2024 - Current
Data Screening and Analysis: Screening over 12,000 records with fellow reviewers and researchers to evaluate the application of AI tools in clinical trial recruitment and retention.
Efficiency Enhancement with AI: Utilized ChatGPT to score and prioritize paper screenings, tripling the efficiency of the research process.
Research Planning and Communication: Proactively communicated with researchers for feedback and suggestions, collaboratively designing the research plan and methodologies, and developing search strategies with librarian staff.
Training and Leadership: Led the training process for new student coworkers and reviewers.
Manuscript Preparation: Drafted manuscripts for submission to peer-reviewed journals.
Master Thesis
Duke University
Durham, US
10.2023 - Current
Data Acquisition and Collaboration: proactively collaborated with model owners at Duke and conduct comprehensive literature research, gathering essential data for simulations.
Data Analysis and Simulation: Analyzed collected healthcare data, running simulations with over 20 scenarios. Created user-friendly visualizations using R Shiny to deliver insights, suggestions, and support to model owners.
Research Coordination and Manuscript Preparation: Actively communicated with supervisors and research associates to clarify and specify research goals, protocols, data sources, and methodologies. Drafted manuscripts based on the discussions.
Research Intern
Fan Li
Durham, NC
07.2024 - Current
Participated in team meetings to discuss research progress and findings related to using EHR to pptimize cardiovascular disease prevention
Data Analyst Intern
McMaster University
Hamilton, Canada
12.2021 - 04.2023
Collected and integrated experimental data from multiple databases, performed data extraction, cleaning and validation
Performed extensive frequency analysis (SAS) and statistical analyses (ANOVA and Chi-Square Test) to access the correlation and causal-effect relationships between treatment and adverse effects
Literature screening and identify over 1000 relevant publications.
Summer Research Intern
Yale University
Yale University
05.2021 - 09.2021
Did extensive literature research to gain domain knowledge, demands and challenges in PDAC analysis and early stage cancer diagnosis
Utilized R to perform preliminary analysis including univariate and bivariate analyses, correlation analyses, data imputation, variable binning and transformation etc
Developed predictive models through multivariate regression and decision trees, identifying LYVE1, REG1B, and TFF1 biomarkers as key predictors for PDAC analysis
Validated models through residual analysis and cross-validation
The developed models exhibited high prediction power (AUC=0.72, KS=0.49), which provided a promising approach for early stage PDAC cancer analysis.