Professional History
Technical Skills
SAS, Python, R, Matlab, STATA, SQL, MS Office (Word, Excel VBA, PowerPoint)
Biostatistician at Sotres-Alvarez Lab
August 2021 - Present
ETL 5 GB pediatrics health data on children's hospital visit as well as personal data from four different hospitals across the US.
Perform linear regression on SAS and test the relation between bioimpedence and Body Mass Percentage for children.
Level the Playing Field Fellowship
October 2021Â - Present
Participate in career advising programs hold by former UNC students.
Aquire key skills for STEM and professional development.
Attend weekly seminar presented by prominent figures in the STEM field.
Map the System UNC Finalist
December 2020 - April 2021
Team leader, study the green space use’s interaction with urban heat islands, as well as the disparity between neighborhoods. Use statistical models and GIS to access the green space distribution in the US.
Data Analysis Research Assistant
September 2020 - December 2021
Extract, Transform and Load (ETL) 1GB turtles profile data and maintain large database operation in a local database
Develop descriptive statistics in Python on 1+ million rows to perform the Exploratory Data Analysis to show the relation of how turtles learn magnetic fields and location, temperature, salinity, etc.
Build machine learning models (Multiple Linear Regression, Random Forest) to recommend recognition of magnetic fields improvement and related factors
Improve model processing efficiency by 90% and increase model accuracy by 20% via ML model selection and tuning
· Present data analysis results and propose strategic solutions to 10+ project stakeholders
Teaching Assistant at Brandeis University
August 2019 - May 2020
Prepared recitation materials, such as PowerPoint and weekly practice problems.
Organized and lectured supported study groups of 50 to 70 students, encouraged and reviewed questions during pretest review sessions.
Offered detailed explanation on core topics. Proctored examinations.
Interviewed and found out prospective student that could work for the professor in the upcoming school year.