projects.

A proof-of-concept web application that combines MCMC Bayesian inference with AI-powered interpretation for agricultural soil analysis

SPARCS is a specialized software tool for the quantitative analysis of 1D Nuclear Magnetic Resonance (NMR) data. This application provides researchers with a statistically rigorous method for accurately characterizing peak parameters within complex spectra.

A suite of high-performance Python implementations for Gaussian Process Regression, Finite Mixture Models, and Hidden Markov Models.

An interactive web application that visualizes how various Markov Chain Monte Carlo (MCMC) algorithms explore probability distributions. Designed for students, data scientists, and researchers to gain intuition about sampling efficiency, tuning parameters, and the behavior of different samplers in 2D space.