Brian Qi

ABOUT

Hi There!

My name is Brian and I'm a third-year student at UC Berkeley studying Computer Science and Data Science.

This Winter, I worked as a Software Engineering Intern at LinkedIn on the Commerce and Enterprise Platform team. The previous Summer, I worked as a Software Engineering intern at HelpWear where I developed and tested critical software for a wearable heart monitoring system.

Currently, I'm also working as a Computer Science Mentor to help students succeed in lower division courses.

I'm passionate about many things tech-related, including software development, data analytics and STEM education.

In my free time, I like to play squash, eat hotpot and experiment with different milkshake flavors. Feel free to reach out to me - I’d love to chat!

SKILLS

Programming: Languages | Frameworks | Libraries

Python, LaTeX

Java, SQL

C#, HTML, CSS

JavaScript, Scheme

Additional Knowledge

○ C, RISC-V

○ Git, Unix, Linux

○ NumPy, SciPy, scikit-learn, Jupyter, pandas, Ray

○ Visual Studio, Eclipse, IntelliJ

○ Mathematica

PROJECTS

Here are some of the software development projects I have worked on in the past
(code available on my github or upon request)

Gitlet

Built a slim version-control system that closely mimics features from Git (i.e. commit, branch, merge, log, status)

Bear Maps

Utilized real-world mapping data to implement the back end that powers the API of a Java web mapping application

Yelp Restaurants

Created a visualization of restaurant ratings using machine learning and the Yelp academic dataset

Scheme Interpreter

Programmed an interpreter for a subset of the Scheme language using Python. Includes features such as define, cond, let, begin, lambda, and mu

Guavabot

A program that tries to efficiently send bots home given restrictions. Our team's algorithm was awarded 3rd place out of 346 teams (CS 170)

Ants vs SomeBees

Engineered my own version of a popular tower defense game. Project is inspired by PopCap's Plants vs Zombies

Spam/Ham Classification

Created a classifier that can distinguish spam from non-spam emails by applying feature engineering to text data