A public-information tool that translates federal court opinions into plain-English summaries non-lawyers can actually follow. Built an end-to-end daily pipeline: automated ingestion from CourtListener's API, AI-powered summarization via Anthropic Claude (three tiers per opinion — one sentence, three paragraphs, and a detailed legal analysis), Postgres database via Supabase, and a Next.js 15 frontend with custom typography and design system. Deployed on Vercel with daily automation through GitHub Actions. Independent project, not affiliated with any court or institution.
Modeled running shoes as thermodynamic systems to understand how energy is managed and heat is transferred in athletic footwear. Applied the Einstein model to explain temperature-dependent behavior of midsole materials like EVA, TPU, and PEBA, and analyzed conduction, convection, and evaporation using Fourier's law. Also examined how carbon-fiber plates and advanced foams improve energy return.
Built a Python framework to minimize renewable energy shortfalls in solar and wind systems. Used stochastic gradient descent with momentum to optimize energy storage allocation, validated through 1,000 Monte Carlo simulations against historical data from 1965–2023. Calculated risk metrics including Value at Risk and 95% confidence intervals.
Designed a Monte Carlo simulation in Python to evaluate real estate valuations under uncertainty. Modeled correlations between rent growth, interest rates, vacancy rates, and maintenance costs using correlation matrices, then ran 10,000 scenarios with discounted cash flow analysis to project property valuations and risk metrics.
Designed and built this website from scratch with a focus on clean design, responsive layout, and maintainable code. Features scroll-driven animations, mobile-first styling, and organized asset architecture. Deployed on GitHub Pages.