Synesis is a Domain-Specific Language (DSL) compiler that transforms qualitative research annotations into canonical knowledge structures.

A comprehensive Python library providing structured, hierarchical exception classes for data science, data engineering, and ML pipeline workflows. Features 40+ specialized exceptions, logging helpers, and production-ready error handling for robust data processing systems.

End-to-End Python implementation of Massacci et al.'s (2025) novel Randomized Alpha Test for high-dimensional factor models. Features robust OLS estimation, Extreme Value Theory-based inference, Monte Carlo simulation engine, and rolling-window empirical analysis. Handles N>T panels with non-Gaussian, heteroskedastic returns.

A modern, secure exam complaint management system built with Next.js 15, TypeScript, and PostgreSQL. Features enterprise-level Row Level Security (RLS), Cloudinary-powered profile management, role-based access control, and real-time notifications. Designed for academic institutions with automatic database setup and responsive UI.