Currently developing AI tools and apps, data/web scrapers, and analytics pipelines in the AI-workflow productivity and nonprofit spaces, with a heavy dash of machine learning. Passionate about building efficient, scalable solutions and exploring the intersection of theory and practical applications. Inspired to push the boundaries of machine learning in neural computing and neurological disorder early detection systems.

Earned my B.S. as an Interdisciplinary Studies major with a focus on computer science, applied economics and management, and agricultural studies. Developed a multi-disciplinary systems thinking approach to complex real-world problems. Interested in technology, organizations, and systems that improve lives.

• Developing full-stack applications with modern frameworks
• Architecting data and web scrapers with contemporary technologies
• Building robust implementations of machine learning algorithms
• Contributing to open-source projects

• Languages: Python, Java, JavaScript, TypeScript, HTML/CSS, SQL
• Frameworks: React, Node.js, Next.js, Spring Boot
• Tools: AI, Git, VS Code, Cursor, Jupyter, JUnit, Firecrawl, Supabase
• Concepts: Machine Learning, Test-Driven Development, Fullstack Development, MCP, Thorough Documentation, DSA, OOP

AI-powered content generation platform that transforms source materials into professional articles through multi-step AI pipelines.

• Tech: Next.js 15, React 19, TypeScript, PostgreSQL, Drizzle ORM, Supabase, Anthropic Claude 3.5 Sonnet, OpenAI GPT 4o, Tailwind CSS, Lexical, Shadcn
• Highlights: Multi-step AI pipeline, intelligent source attribution and weaving, enterprise multi-tenant architecture with usage analytics, comprehensive export capabilities (PDF/DOCX/email), real-time processing with live status updates

Scraper for nonprofit revenue and executive compensation data for a selected state.

• Tech: Python, API Interaction, OCR Image-PDF Parsing, Pandas, Excel
• Highlights: Smart data collection algorithms, Scanned 990 IRS form parsing, Beautiful business-ready spreadsheet reporting

Advanced machine learning framework for Parkinson's disease identification utilizing vocal biomarkers with streamlined data processing, automated model development, and comprehensive performance assessment.

• Tech: Python, Scikit-learn, Pandas, Matplotlib, Seaborn, Jupyter, FastAPI, Railway
• Highlights: Scalable architecture with data refinement and feature optimization, thorough model assessment achieving 94.9% precision, intelligent feature selection leveraging Random Forest importance metrics, robust validation framework incorporating multiple algorithms (Logistic Regression, Random Forest, SVM)

Graph algorithms implementation for maze navigation using Dijkstra's shortest path and optimized DFS/BFS traversal strategies.

• Tech: Java, Graph Theory, Concurrent Programming
• Highlights: Pathfinding optimization, thread synchronization, performance tuning

A Python toolkit, designed for AI-workflow productivity startup Astral AI, that extracts and organizes web documentation into well-formatted markdown files using the Firecrawl SDK.

• Tech: Python, Firecrawl SDK
• Highlights: Crawler and scraper functionality, well-formatted markdown files for efficient user and machine learning/LLM parsing, navigable index generation for extracted documents

A flashcard website designed to optimally help a user learn vocab words... and to help me study for the GRE :)

• Tech: JavaScript, HTML/CSS, Excel/CSV, SheetJS, PapaParse
• Highlights: Offline use after initial data import, individual word performance statistics, beautiful and simple interface, export progress to Excel or CSV

• Advanced machine learning and statistical learning methods
• Fullstack development
• System design patterns
• Development experience optimization technology

• Astral AI (client full-stack AI web apps, foundational platform code)
• Replicating an MCP Integration service for AI applications
• Portfolio website (neural computing inspiration styling)
• Machine learning and neuroscience blog (styling, database/CMS, more content)
• Parkinson's detection machine learning project (model improvements, frontend interactivity, data visualization)
• Nonprofit revenue scraper (improved PDF parsing, robust executive compensation parsing, dashboard)

• Email: [cameronbrady1527@gmail.com] or [cab495@cornell.edu]
• LinkedIn: [https://www.linkedin.com/in/cameron-brady-5770431b5/]
• Portfolio: coming soon

💡 Fun Fact: When I'm not coding, you can find me substitute teaching K-12; tutoring in math and science; training for a race; learning and reading books on neuroscience, machine learning, meditation, and more; and volunteering.

⭐️ Feel free to explore my repositories and don't hesitate to reach out for collaborations or opportunities!