Kelechi.

Quantifying uncertainty, then building the software that uses it.

Bayesian inference, scientific modeling, and the data products that come out of it. Applied mathematician, Knoxville.

Work, sorted by kind

product2026

GridAlmanac

Programmatic reference of 15,000+ U.S. power plants, owners, and the interconnection queue, from EIA and LBNL data.

live
product2026

The Grid Atlas

Interactive map tracing electricity pricing from plant to node to hub to bill, with scenario sliders and a guided trace.

live
research2026

Feed intake in automated milking systems

Machine learning models to estimate feed intake in dairy cattle. Applied Animal Behaviour Science 303:107079.

published
tool2025

MCMC Lab

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.

live
tool2025

Agri-Bayes

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

live
tool2024

Bayesian Models

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

archived
tool2024

Pathfinder

A recursive web crawler that captures full-page screenshots along navigation chains

archived
research2023

Statistical Parameterization of Analytical Resonance in Chemical Spectroscopy

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.

archived