I'm a first year Master's student at Stanford University, studying CS with an AI specialization. Previously, I graduated from UC Berkeley with EECS Honors in three years, where I conducted research at the Berkeley Artificial Intelligence Research Lab improving machine translation for low-resource Asian languages through the MITRA Project and GUI Agent Automation in collaboration with Panasonic. I've worked as a software engineering intern at Google, Aurora, a self-driving truck company, and the Penn Wharton Budget Model. I'm passionate about increasing opportunities and accessibility for female-identifying engineers, and served as the Vice President of Corporate for Berkeley's Society of Women Engineers.

getExperience()

Software Engineering Intern @ Google

May 2026 - August 2026

Software Engineering Intern @ Aurora

May 2025 - August 2025

Undegraduate Researcher @ Berkeley Artificial Intelligence Research Lab

May 2024 - May 2026

Teaching Assistant @ Probability and Random Processes (EECS 126)

July 2025 - May 2026

Software Engineering Intern, prev. Research Intern @ Penn Wharton Budget Model

Apr 2022 - Jan 2025

Vice President of Corporate Relations, prev. Startup Spring Officer, Professional Development Month Officer, Public Relations Officer @ Society of Women Engineers

Sept 2023 - May 2026

Tech Mentor, Junior Mentor @ Computer Science Mentors

Jan 2024 - Jan 2025

Executive Advisor, prev. Executive Director & Flute Instructor @ Notelove

Aug 2019 - Present

getProjects()

CS180: Computational Photography and Computer Vision

As part of Fall 2025 CS 180, I completed a variety of projects implementing recursive image pyramids, image filters for blurring and isolation of frequencies, autostitching photo mosaics with homography and feature detection, NERF, and diffusion models.

Tools used: Python, Scikit-image, Pytorch

image blending of Avery and survivor contestant Jonathan

Survivor Machine Learning Winner Prediction

As a huge Survivor fan, I have always wondered whether it is possible to predict who will win! In this project, I utilized open-source Survivor data and a multivariate logistic regression model to predict which contestants would win Survivor.

Tools used: pandas, R, Scikit-learn

data visualization showing percent immunity won by Survivor winners and non-winners

Personal Website

As part of the CS Kickstart program at UC Berkeley, I coded this personal website as part of my final project. Some of my favorite features include the typing carousel and background with floating squares.

Tools used: HTML, CSS, JavaScript

screenshot showing a purple home page of Avery Chen's personal website

getInterests()

Outside of tech, I'm interested in a variety of things!

a girl stands in a white dress under a stone arch