I'm a computer science student at Georgia Tech who is interested in developing technology that solves real-world problems. At Cruise, I improved the reliability of core infrastructure tools used by 1000+ autonomous vehicle developers on a daily basis to remotely connect to in-house virtual machines. While interning at Fidelity Investments, I worked on developing highly-scalable cloud infrastructure and decreased cloud deployment time by over 17x. As a software engineer intern at Odynn, I assisted in developing the application's proprietary back-end with the CTO to allow consumers to fully leverage their credit card rewards. Back home, I co-founded Scholastician, a student-run organization aimed at providing personalized tutoring by matching students to certified tutors, which received a Congressional Commendation by my local House Representative (TX-03) and was featured by local news channels. In my free time, I enjoy building projects and watching sports.
Prior to attending Tech, I also interned as a research assistant at the University of Texas at Austin under Dr. Xuesu Xiao where I improved the efficiency of path-planning for high-dimensional robotic arms using machine learning.
Drove 22.8% reduction in config issues for 1800 devs via Golang diagnostic application and slashed dev issue resolution time by 54% via automated file generation and new standardized reporting procedure
Automated migration of 200+ apps from old (Jenkins/uDeploy/Concourse) to new cloud infrastructure (Jenkins Core/Terraform) and reduced migration onboarding from 4-6 weeks to 1-3 days using AWS Step Function/DynamoDB/Lambda/CloudWatch
Eliminated 100+ hours of manual effort annually by updating MongoDB credit card database using scraped data and reduced integration delay from 1 week to 1 day by creating automated pipeline to notify developers of card issues
Optimized path-planning algorithm for high-dimensional robotic arms by leveraging convolutional neural networks. Generated 10,000 workspaces & configuration spaces by engineering robotic arm graphical simulator using Python. Designed convolutional neural network using Keras & TensorFlow to decrease path-planning time versus Dijkstra's
Bachelor of Science in Computer Science, Artificial Intelligence and Information Internetworks Concentrations.
Relevant Coursework: Advanced Algorithms, Data Structures & Algorithms, Machine Learning (G), Computer Vision (G), Systems & Networks, Computer Architecture, Object-Oriented Programming, Software Design
When my high school's tutoring system fell apart due to a shift to online school during the pandemic, I sought to find a solution to the problem to help the people that no longer had access to tutoring for free from the school library. As a result, I created a full-stack web application to pair students to tutors for free, which allowed students from my high school to be paired with NHS volunteers. After this reached my school, I scaled it by streamlining user registration to the DFW metroplex and eventually 5 different states across the country, notably California and Texas. As a result of my efforts, I was awarded Congressional Commendation from TX-03 Representative for outstanding community impact within the Dallas-Fort Worth area.
As part of my Phase 4 project for my databases class (CS 4400), I created a fully-functional full-stack application using React.js, Express.js and Node.js (web technologies), which was connected to a MySQL RDBMS database. This application allowed us to monitor and update an express restaurant drone delivery system around campus including the pilots, employees, services, restaurant owners, and ingredients for the restaurants behind the scenes supporting the system. This project allowed me to learn the fundamentals of how to create an application where the front-end heavily intertwines with the back end and where there are many constraints when entering information into the database. For example, one of the constraints in the database was that a person could not assume multiple responsibilities (i.e. being a restaurant owner as well as a pilot or employee). The process of accounting for edge cases was not trivial since many of the components were closely related.
