Ignatius Martin
I design and build software that solves real problems — from distributed systems to delightful user interfaces.
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I design and build software that solves real problems — from distributed systems to delightful user interfaces.
I'm a Computer Science student at the University of Florida, drawn to the intersection of systems thinking and elegant product design.
Whether I'm optimizing a backend service or obsessing over UI interactions, I care deeply about the craft behind software. I thrive in environments where ideas move fast and quality still matters.
Architected cross-platform modules in React Native, TypeScript, and Convex for a product serving 5K+ monthly active users. Cut crash rates 15% through state optimization and CI/CD-integrated profiling. Drove a 25% faster SDLC velocity across 20+ deployed features using Agile/Scrum and TDD with 95% test coverage.
Developing deep learning pipelines with TensorFlow/Keras, reaching 92% accuracy on linguistic pattern recognition over 100K+ records. Improved Precision/Recall by 18% via tokenization optimization and deployed three end-to-end ML prototypes with scikit-learn, improving inference speed 40%.
Reduced page load time 32% on a React SaaS product via lazy loading and dependency trimming. Built responsive UIs with Tailwind CSS that drove a 45% lift in user engagement. Integrated CI/CD pipelines using Docker and GitHub Actions, cutting deployment friction by 60%.
Scalable cloud-native platform with 99.5% uptime, powered by containerized microservices and AWS IAM security. Enhanced data throughput by 60% via async RESTful integrations and a Redis caching layer.
Stock recommendation app that scores equities across momentum, stability, income, and value factors. Users select sector, risk level, and duration to receive up to 5 ranked picks from 62+ stocks across 7 sectors, refreshed nightly via yfinance.
Predictive model using a hybrid CNN–LSTM architecture, achieving 68% validation accuracy through rigorous cross-validation tuning on historical NBA game data.
NBA player prop analysis tool featuring distribution modeling, expected value calculation, line movement tracking, and an AI-powered chat assistant for edge identification.
I'm open to internships, research collaborations, and interesting side projects. Drop me a line.
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