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Built the official ColorStack @ UCSD website to showcase the community, events, and impact of Black and Hispanic software engineers at UCSD

Web Development•Next.js 16•React 19

I built the official ColorStack @ UCSD website, the first website for this 2-year-old chapter of a national nonprofit dedicated to increasing the number of Black and Latinx Computer Science graduates entering top tech companies. The website features a comprehensive event calendar for technical workshops, career development sessions, and community building events, a member directory showcasing the community, and a blog section to highlight the work and achievements of members. I implemented sections for Our Values (Community, Excellence, Impact), What We Do (Technical Workshops, Career Development, Mentorship Program, Community Building), and Our Board structure (Executive, Development, Outreach, Finance boards). The site is built using Next.js 16, React 19, TypeScript, Tailwind CSS, and Prisma ORM for database management, with responsive design and modern UI components that reflect the community's mission of excellence and impact.

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Built a comprehensive e-commerce platform to expand STEM education and technology access to underprivileged communities

Web Development•Next.js 15•React

I developed a full-stack e-commerce platform for my nonprofit foundation dedicated to expanding STEM education and technology access to underprivileged communities. The platform features a complete shop system with print-on-demand merchandise through the Printful API, a donation system with both one-time and recurring contributions via Stripe, and automated email notifications using the Resend API. I implemented NextAuth.js v5 for secure authentication, built a comprehensive order management system with webhook handlers for both Stripe and Printful, and created a partnerships program to facilitate organization collaborations. The platform includes guest checkout support, persistent shopping carts, real-time inventory management, and a social sharing system to amplify the mission. With 50% of all profits directed to supporting digital equity initiatives, the website serves as both a revenue generator and community hub for creating creators rather than renters in the digital space.

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Trained a custom YOLOv8 model to identify 9 specific desk objects with 80% training accuracy

AI•Object Detection•YoloV8

I created a custom YOLOv8 object detection model trained on 351 hand-labeled images across 9 desk object classes. The project involved recording 5 training videos from multiple viewpoints (birds-eye, front, horizontal, left, right), extracting frames every 2 seconds, and manually annotating each image. I implemented a complete pipeline including JSON-to-YOLO format conversion, dataset splitting (80% train, 20% validation), and model training for 84 epochs. The final model achieved a fitness score of 0.7944 and successfully detected all target objects in real-world video scenarios after confidence threshold optimization.

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Analyzed corporate vs podcast viewership from 2020 to 2024 to determine whether a decrease in corporate viewership coincides with an increase in podcast viewership

Data Science•Statistical Analysis•Python

As part of a group project for my Data Science class at UCSD, I led the development of a comprehensive data pipeline to analyze corporate media vs. political podcast viewership from 2020-2024. I built three main systems: 1) A Selenium-based web scraper for Variety.com to extract corporate media viewership data, 2) A Wayback Machine API integration to gather Spotify podcast rankings from 2021-2024, and 3) A YouTube Data API pipeline with intelligent caching to fetch podcast viewership metrics. The project involved processing 1,040 observations across multiple data treatments, implementing outlier detection using IQR, Modified Z-Score, and Z-Score methods, and conducting comprehensive statistical analysis including ANOVA, Kruskal-Wallis tests, and effect size calculations. I handled significant technical challenges including API rate limiting, data standardization, and creating algorithms to filter valid podcasts with consistent yearly data.

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