My name is Chen (Eric) Xue.
I started studying in the U.S. by myself when I was 14, living with three different host families, familiarizing myself with U.S. culture, and adapting to different environments. In college, my passion for data science leads me to learn technology outside of the classroom. I use my free time to analyze data with my team, learn together, combine everyone's perspectives, and be the mouth to present our findings.
A few interesting things about me. I started learning Peking Opera when I was 10. I love eating and cooking. My girlfriend and I taste many restaurants in Atlanta, and I enjoy cooking for her at home. I also like biking, but it is quite unfortunate my bike got stolen recently. Lastly, I enjoy sharing happy life stories with others and listen to theirs. Embracing my happy life and celebrate others.
(Scikit-learn, Keras & TensorFlow)
Udacity Free Trial Screener A/B Testing
At the time of this experiment, Udacity courses currently have two options on the course overview page: "start free trial", and "access course materials". In the experiment, Udacity tested a change where if the student clicked "start free trial", they were asked how much time they had available to devote to the course. If they indicated fewer than 5 hours per week, a message would appear indicating greater time commitment is needed and take students to free course materials. Udacity wonders if setting a clearer expectation for students upfront can reduce the number of students who left the free trial, which could improve the overall student experience and improve coaches' capacity to support students who are likely to complete the course.
LendingClub Loan Default Prediction, Deep Learning
LendingClub is a US peer-to-peer lending company, headquartered in San Francisco, California. It was the first peer-to-peer lender to register its offerings as securities with the Securities and Exchange Commission (SEC), and to offer loan trading on a secondary market. LendingClub is the world's largest peer-to-peer lending platform.
This data analysis aims to build a neural network model that can predict whether or nor a borrower will pay back their loan based on historical data on loans given out with information on whether or not the borrower defaulted. This way in the future when we get a new potential customer, we can assess whether or not they are likely to pay back the loan.
Standard Bank Data Science Virtual Experience Programme, Machine Learning
As Africa’s biggest lender by assets, Standard bank aims to improve the current process of applying for a home loan, which involves loan officers having to manually process home loan applications. This process takes 2 to 3 days to process upon which the applicant will receive communication on whether or not they have been granted the loan for the requested amount.
To improve the process Standard Bank wants to make use of machine learning to assess the credit worthiness of an applicant by implementing a model that will predict if the potential borrower should get the loan based on historical information, and do this such that the applicant receives a response immediately after completing their application.
[Emory DataFest 2022]
Understanding players’ behaviors via Elm city Stories:
An Analysis on the usefulness of the game as an evidence-based assessment tool
Elm City Stories is an educational game that aims to identify teenagers who may need help in the future based on their performance in the game. This data analysis evaluates the game’s ability to understand and predict potential drug usage by correlating participants’ performance in the drug-related aspects of the game with their S5 survey result, which indicates their ability to resist drugs in the real world. We realized the “Dunning-Kruger Effect” and the “Imposter Syndrome” might play a role in the correlation study, and the S5 survey might have reliability issues.
[Fall Data Challenge 2021]
Combating the Food Insecurity in the US:
A County-level analysis and recommendations
Food insecurity is a severe problem in the United States that affects nearly 30 million adults and 12 million children. This research analyzes the true effects of relevant factors in relation to food insecurity in the United States at county-level, and provides corresponding recommendations to overcome the controlling factors in the food insecurity issue in the U.S..
Quantitative Sciences & Computer Science
Emory University, GPA 4.0/4.0
Aug 2020-Dec 2023
Cloud Data Tech Intern
Jun 2021-Aug 2021
Oxford College, Emory University
Aug 2021-Feb 2022
Undergraduate Teaching Assistant
QTM department, Emory University
Jan 2022-May 2022
Queen Savvy Lab, Nell Hodgson Woodruff School of Nursing at Emory University
VC & Business Analyst Summer Intern
HP Tech Ventures
Jun 2022-Aug 2022
PhotographyI started learning photography in high school. I was the school event photographer, working closely with media office and yearbook. I took pictures of football game, prom, drama, and also for my own hobby. I won the silver key in the scholastic competition in my junior year and began selling my photos for fund raising purposes.
Peking OperaI started learning Peking Opera when I was in second grade. My team and I performed in the National Center for the Performing Arts in China and won the First Place in National Opera Competition. After I studied abroad, Peking Opera becomes one of my biggest hobbies and one thing I missed most about China. I started an E-News Letter to propagate Peking Opera, contributing to the continuity of this art.
CookingGood food is what makes my life meaningful and full of happiness. I love cooking, especially for others so I can share this happiness. In short, I work hard so I can eat well. lol