JESUS RODRIGUEZ
I’m a software engineer passionate about finding creative solutions to algorithmic problems in computer systems and AI/ML. Currently a junior at Brown University studying Computer Science and Mathematics. Outside of the classroom, you can find me developing solutions for student organizations with Full Stack at Brown, or playing the guitar in my dorm.
EXPERIENCE
Summer 2025
Walmart - Incoming Software Engineer II Intern
June 2024 - August 2024
Center for Computation and Visualization - Data Science Intern
Developed and deployed a Docker container for NVIDIA's Parabricks framework on a high-performance computing cluster. Enhanced code performance by leveraging GPU clusters, reducing runtime from 3 hours to 30 minutes.
March 2024 - Present
Embrace Medical - Machine Learning Engineer
Developing a machine learning model for medical prosthesis through advanced data analysis and algorithm optimization. Designed and implemented a React-based website to improve user experience and mobile accessibility.
March 2024 - Present
Serre Lab - Science Communicator and Web Designer/Developer
Redesigned and implemented an outdated lab website using Figma and React, enhancing user experience and visual appeal. Created engaging educational content on neuro AI for social media, simplifying complex concepts for a broad audience.
February 2024 - Present
Full Stack at Brown - Software Engineer
Developed a GraphQL database integrated with a content management system. Built the client's website from scratch using React and TypeScript, translating designers' visions into functional components.
July 2022 - August 2022
OppNet Summer Science Research Program - Researcher
Conducted in-depth research on music therapy as an intervention for individuals with disabilities. Developed a comprehensive literature review on advancements in music therapy and disability studies to support academic research.
PROJECTS
Integrating Neural Networks with Linear Regression to Enhance Control Vectors in Social Sciences
This project explores the integration of neural network-based feature extraction with traditional linear regression models to improve prediction accuracy in the social sciences. This approach aims to maintain the interpretability of linear models while leveraging the predictive power of neural networks to enhance feature representation. This method could be particularly useful in fields where the interaction effects of variables are significant but difficult to model linearly.
Python
TensorFlow
Web Chat Application with RESTful API and Websockets
This project involved creating a web chat application inspired by platforms like Discord and Instagram. It features chat room creation, private messaging, and user management using a RESTful API and websockets. The frontend was built with React, while the backend utilized GoLang with the Gin framework for endpoints, gorilla-websocket for live chat, and a custom user authentication system. The project demonstrates the integration of modular frontend components with backend logic to handle real-time messaging and user interactions.
React
GoLang
Gin
Websockets