Annie Xu

I’m currently a first-year graduate student at Columbia University, pursuing a master’s degree in Computer Science. I earned my bachelor’s degree in Computer Systems Engineering from Rensselaer Polytechnic Institute, where I developed a strong foundation in software development, system architecture, and data-driven solutions. I’m a software engineer with a passion for building intuitive and scalable applications.

My goal is to craft technology that solves real-world problems while delivering seamless user experiences. I’m particularly interested in full-stack development, UI/UX design, and cloud computing, and I aim to use my skills to create solutions that are both powerful and accessible.

When I’m not coding, you’ll probably find me on the badminton court, art crafting, or exploring new ideas through music, side projects, and creative problem-solving.

Aug 2023 — Dec 2023

Software Engineering Intern • MVP Health Care

Developed an interactive Choropleth map to visualize pharmacy deserts in New York State. Improved medical adherence prediction accuracy by 15% through machine learning models. Integrated a digital twin of healthcare infrastructure to simulate pharmacy access patterns. Worked with a cross-functional team to clean datasets, ensuring accurate pharmacy accessibility metrics.

Overleaf

React

GIS

Scikit-learn

SQL

Agil Development

Python

Data Analysis

May 2023 — Aug 2023

Systems Analysis and Exploitation Intern • Assured Information Security

Performed efficiency assessments on a cloud hypervisor forensics platform, leading to a 20% improvement in analysis time. Crafted a radio string injection attack script for an open-source RF and reverse engineering framework using C++. Developed comprehensive test scripts to evaluate the framework’s functionality and enhance its CI/CD capabilities.

Linux

Reverse Engineering

Python

Jenkins

Unit Testing

Hypervisors Forensics

Cloud Computing

May 2022 — Aug 2022

Application Engineering Intern • Xallent Inc.

Engineered software to extract electrical and mechanical properties, resulting in a 40% improvement in data accuracy. Designed and implemented PID control and feedback routines to enhance probe-device interaction. Developed a Python-based data acquisition system for real-time collection, processing, and visualization of measured data.

Python

Matlab

LabVIEW

SQL

Plotly

RTOS

C++

View Full Résumé

String Swift – Stringing Request App

A cloud-based application designed to enhance the racket stringing experience for badminton, tennis, and squash players. The platform features an intuitive front-end interface for users to place orders, track real-time updates, and process secure payments. Front-end functionalities are seamlessly integrated with the back-end system to ensure efficient data synchronization for stringers. Deployed on AWS to optimize performance, scalability, and accessibility.

CozyQuarter – Dorm Review Hub

Led a team to develop an interactive web platform that enables students to post and explore dorm reviews, enhancing transparency and decision-making for on-campus housing. The platform features a user-friendly map for seamless visualization of dorm locations and feedback. A robust database system, built with MongoDB, efficiently stores reviews, ratings, and photos, ensuring fast and reliable data retrieval. The project emphasized accessibility, user engagement, and intuitive design.

GitGud – Social Welfare API

Led development of a social welfare API to streamline resource management for shelters, clinics, and outreach programs. Built with Node.js and MongoDB, featuring secure authentication with JWT and real-time service updates via a dynamic map interface. Integrated external APIs to enhance data accuracy. Deployed on Google Cloud Platform (GCP) for scalability and reliability.

NeRF-or-Nothing

A web application that leverages Neural Radiance Fields (NeRF) to generate novel 3D views of complex scenes from 2D images. Back-end development focused on computing extrinsic and intrinsic camera parameters from COLMAP output to enhance 3D reconstruction accuracy. A web server worker queue was implemented using RabbitMQ to efficiently manage Structure-from-Motion tasks, optimizing computational performance. The project demonstrated expertise in computational photography and real-time 3D rendering.

Research & Development