BAyesian Model-Building Interface (Bambi) in Python.
The official implementation of "Joint Modeling of Image and Label Statistics for Enhancing Model Generalizability of Medical Image Segmentation" via Pytorch
A professional, research-grade comparison of Gaussian Copula and Variational Autoencoder (VAE) methods for synthetic tabular data generation. Includes full evaluation pipeline with distribution overlap, correlation analysis, PCA projections, pairplots, metrics, and automated visual reports.
A collection of scripts used for modeling global daily maximum surges
Implementation is to use gradient descent to find the optimal values of θ that minimize the cost function.
Python package for conducting power analysis for experiments using regression and/or clustered data.
Fitness estimates of SARS-CoV-2 variants
Pure-Python library of heavy-tailed probability distributions (Pareto, Burr, LogNormal, etc.) built from first principles.
Data science projects created using actual data, using Python and R.
Health and Economic Data Dashboard with Forecasting
Details the data modeling techniques used, the functionality of the output, and an in-depth idea of how a plan finder works based off of user inputs.
A Machine Learning modeling pipeline that predicts customer churn of an organization based on customer historical behavior
AI-powered system that converts offline fantasy football draft board photos to complete digital results. Universal manufacturer compatibility through color detection + intelligent player matching with direct ESPN upload.
Entity prioritization and escalation detection using GLMM statistical models
📈 Create a simple product sales forecast system in Python with Tkinter, featuring custom calculations and different chart visualizations for data insights.
Pi estimator based on the Monte Carlo method
Graduate-level course on Scientific Computing (CIMAT, Spring 2025). Includes assignments and simulations on Monte Carlo methods, MCMC algorithms (e.g., Metropolis-Hastings, t-walk), inverse problems, and Bayesian inference using Python.
Automatically determine trends, correlations, and feature selections given dataset(s)
NLP: Performing sentiment analysis on text-tweet data from Twitter.
The interface library for probabilistic modeling in HEP
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