Here, the goal is to use spatially-resolved transcriptomics to improve the diagnosis accuracy of cancer metastasis. What I did specifically:
Analyzed spatial autocorrelation of colorectal cancer genomics data in Python with SpatialDE and SPARK-X
Developed convolutional neural networks and graph attention networks with Python/Pytorch to predict spatial expression of cancer-related genes with an AUROC of up to 0.89
Also developed some experience with Slurm/high performance computing. Work soon to be submitted to a conference.
Internship with Army Research Lab
June 2021 – August 2021; with Dr. Ei Brown
My primary research goal was to measure the efficiency of various laser crystals by detecting the amount and wavelengths of emitted light from each crystal. What I did specifically:
Write Python programs to automatically detect the decay time of an emitted signal. This automation reduced analysis time by ~90%.
Create a real-time spectrum analyzer that enabled us to discover emissions peaks more efficiently, and decompose a single decay signal into various component decay signals
November 2020 – November 2021
Project Caelus is aiming to be the first high school team to create a liquid-fueled rocket. I wrote C++ code to interface between Arduino and remote ground control software and integrate low-level sensor data in a read-control-actuate loop. I also helped optimize some printed circuit boards with KiCAD. The software was used to control valves during cold flow tests.
From April 2020 to April 2021, I volunteered at a computer science tutoring nonprofit called Codefy. I taught courses in Python and web development, and hosted workshops where students learned the fundamentals of machine learning, detected and classified traffic signs using computer vision, and developed games. I also served as a mentor, individually helping students learn Python, as well as leading courses in website development. I also developed an enrollment system that served thousands of students.
As a member of the student government, I rebuilt the main website with Typescript and React and built a website where students can share study guides. I also choreographed a hiphop dances for my year and organized other homecoming events.
Cool Things I've Made
This is an open-source educational content website that my friends and I built. Educational content can be imported from GitHub and is updated automatically whenever contributors make changes. It includes animations and interactive content to cater to different learning styles. Uses React and Express as its frontend and backend frameworks, and MongoDB for data persistence.
StreetSweep is an app that my friend and I created for a hackathon with the goal of helping policymakers and volunteer organizations by creating a heatmap of the prevalence and type of trash at each location. It uses class-agnostic object detection with a model adapted from a ResNet classifier to automatically detect garbage in photos of street litter.
An app to simplify carpooling: students can easily find people to carpool with for after-school events. 300+ users. Worked with school administration and sports coaches to get schoolwide adoption. Helps students who live far away from a school to have the same access to after-school activities as people who live nearby, especially if they are unable to drive themselves. Stack used: Frontend: Typescript React Backend: Node.js/Express, Prisma ORM, PostgreSQL database Hosting: DigitalOcean droplets, VPC for database security
An app that enables the disabled to control their computer mouse with their eyes: after a quick calibration step, the computer would detect which section of the screen they were looking at with 90% accuracy and move the mouse there. Then, via voice recognition provided by Google Cloud, they could click on those parts of the screen, type, search the web, and perform other tasks. Won 1st Place at the HooHacks 2020 Hackathon, an official hackathon organized by students at the University of Virginia. Utilized Haar cascades, DLib facial recognition, a custom iris detection algorithm made with OpenCV, and voice recognition from Google Cloud.