nice to meet you, i'm
Annie Liu


Hi! I'm Annie Liu (she/her), a second year undergrad at MIT pursuing a major in computer science. I'm interested in full-stack development and data science, but that's not all: in addition to coding skills, I love to write stories. Although computer science and writing may seem as different as anything gets, I believe that the creativity and storytelling involved in writing is important in technology as well. Code should tell a story, so other engineers can understand the flow. You need the same analytical skills in coding to stand the test of time as you need to prevent plotholes in stories. After all, you communicate with computers the same way you communicate with the people around you. The only difference is, instead of English, it's in Python. Whether it's through English or Python, I hope to make a difference in whatever I do.


Lyrical Notes

A guessing game from listening to a 30 second preview of a song from Spotify

TECHNOLOGIES: Node, React, Spotify Web API

Mapping Visualization

An interactive map that displays neighborhoods in NYC, a filter legend based on user-selected properties, and a feature that allows you to find the nearest hospital from a specific test marker.


Creative Learning Tool
2020 UROP @ MIT Media Lab (Lifelong Kindergarten Group)

A creative learning tool to help teachers and educators work and learn more creatively and interactively, since current tools do not address the issues that they face.

TECHNOLOGIES: HTML, CSS, Javascript (jQuery, Node.js, EJS), MongoDB, Mongoose

Open Streets
MLH Best Use of MongoDB Winner @ TechTogether Boston 2020 Hackathon

A crowdsourcing platform that promotes more clean, connected, and collaborative communities by allowing users to post issues they notice in their surrounding locations, share details about the assistance that may be required, and automatically update the addresses and dates of when the posts were made.

TECHNOLOGIES: HTML, CSS, Javascript (jQuery, Node.js, EJS, Leaflet.js), Nominatim, MongoDB, Mongoose

Machine Learning Research
2019 Regeneron STS Scholar

A machine learning model for protein subcellular localization predictions to help identify drug targets and contribute to drug repurposing efforts for many protein dysfunctional diseases, including cancer, asthma, and Alzheimer's.

TECHNOLOGIES: Python (Scikit-learn, TensorFlow, Keras)