A production-ready financial analysis tool that runs sophisticated technical indicators (MACD, RSI, Bollinger Bands) against historical stock data and surfaces buy/sell signals through an interactive Streamlit dashboard. Containerized via Docker to eliminate TA-Lib C-library setup friction, with analytics logic fully decoupled from the visualization layer for maintainability. Includes a theoretical profit maximization engine to back-test signal accuracy against historical price data.

A CLI-based student records system built in C using custom data structures — hash tables for O(1) ID lookups, a stack-based undo system for state recovery, and role-based access control separating Staff (write) from Student (read-only) permissions. Automated regression testing written with the Tcl/Expect framework. Demonstrates low-level memory management and systems design without relying on higher-level language abstractions.

A full-stack financial dashboard with a FastAPI backend and Next.js frontend that delivers delayed stock metrics, interactive price charts, and benchmark comparisons against the S&P 500 across YTD, 1Y, 3Y, and 5Y timeframes. Pydantic models enforce strict schema validation between the Python backend and React frontend. A custom date-alignment algorithm using pytz and relativedelta accurately maps historical price points to the nearest US trading day.