Software

I enjoy building open-source tools for science, mostly at the intersection of statistics, machine learning, and computational mathematics. Most projects are developed in R and/or Python, with their computational cores written in C++ to ensure speed and efficiency. I focus on clear APIs, reproducible results, and practical performance. Click a package name to visit its documentation site, when available.

Statistical & Machine Learning

Package Repo Description
CovTools CRAN (R)  GitHub Statistical Tools for Covariance Analysis
filling CRAN (R)  GitHub Matrix Completion, Imputation, and Inpainting Methods
Rdimtools CRAN (R)  GitHub Dimension Reduction and Estimation Methods
repsim Python (PyPI)  CRAN (R)  GitHub Measures of Representational Similarity
SBmedian CRAN (R)  GitHub Scalable Bayes with Median of Subset Posteriors
SHT CRAN (R)  GitHub Statistical Hypothesis Testing Toolbox
T4cluster CRAN (R)  GitHub Tools for Cluster Analysis

Foundational Mathematical & Computational Routines

Package Repo Description
maotai CRAN (R)  GitHub Tools for Matrix Algebra, Optimization and Inference
Rlinsolve CRAN (R)  GitHub Iterative Solvers for (Sparse) Linear System of Equations
T4transport CRAN (R)  GitHub Tools for Computational Optimal Transport
tvR CRAN (R)  GitHub Total Variation Regularization for Signals and Images

Network Analysis

Package Repo Description
graphon CRAN (R)  GitHub A Collection of Graphon Estimation Methods
NetworkDistance CRAN (R)  GitHub Distance Measures for Networks

Geometry & Topology

Package Repo Description
CORRbox MATLAB  GitHub Scalable Learning with Correlation-based Functional Networks
Riemann CRAN (R)  GitHub Learning with Data on Riemannian manifold
RiemBase CRAN (R)  GitHub Functions and C++ Headers for Computation on Manifolds
SPDtoolbox MATLAB  GitHub Geometric Learning of Brain Functional Networks
TDAkit CRAN (R)  GitHub Toolkit for Topological Data Analysis