Hi, I'm Josh!

Current status:
Studying computer science and business
at the University of Pennsylvania

I am a junior at Penn pursuing a dual degree between Penn Engineering and The Wharton School. I've worked as a data science intern at the CDC, undergraduate researcher at Penn Medicine, and web developer for the Korean Language Department at Penn before. I am currently a teaching assistant at Wharton for an introductory statistics course (STAT 4300). Last summer, I worked at Principal Financial Group as a software engineer intern on the company's individual solutions team. Following a successful internship, I am now working part-time with the company during the semester.

My Experience

Here's what I've done professionaly so far!

Software Engineer Intern @ Principal Financial Group

I worked on a client dashboard for individuals to enroll in a robo-investment service based on their risk aversion. On the frontend, I worked with Next.js in TypeScript React to improve web accessibility. For the backend, I implemented API calls in Java that interact with a NoSQL database — all within Spring Boot microservices.

During the company's intern hackathon, I assumed the role of technical lead for my team. We built a React web app that automates business task assignments, using AWS (Lambda, API Gateway, S3) and Llama 3 endpoints.

Data Science Intern @ CDC

I created programs in R that analyze which characteristics of labs or chemical analytes affect lab performance in the mandatory inspection tests conducted by the CDC. Here, I was able to learn and hone my skills in data engineering, statistical analysis, and data visualization.

Web Developer @ Penn

I designed web-books in HTML/CSS for the Korean Language Department's text book series
("You Speak Korean!").

Teaching Assistant @ Penn

I hold weekly recitations to review material with students, grade assignments, and conduct office hours to provide help with Python/R homework for statistics (STAT 4300) and biological data science (ENM 3750) classes.

Undergraduate Researcher @ Penn Medicine

I learned about machine learning using Python libraries like Tensorflow, and Seaborn. With this knowledge, I tested existing machine learning models and consolidated electronic/physical patient data entries.

Portfolio

Projects made with passion - click project names for Github repository!

Retail Car Price Prediction Program

  • This application analyzes 55,000+ data entries of car sale history and predicts car prices based on make year, model, odometer readings, etc.
  • Machine learning models such as Linear Regression, Random Forest, and Gradient Boosting were used. Feature engineering and fine-tuning was performed as well using one-hot encoded PCA and GridSearchCV.

Robot Compatibility Matching App

  • This Android App programmed in Java was used in the FIRST Robotics Competition to collect real-time data input that is used to assess compatibility of a team's robot with another team. SQLite was also incorporated to organize the inputs and produce conclusions from data analysis.

Bioinformatics Toolkit

  • This program illustrates the DNA transcription/translation process through a graphic user interface coded in Python (Tkinter).