What I do
In my current project, I build modeling and machine-learning pipelines to turn large spatiotemporal livestock movement data into realistic network “digital twins” and decision-relevant insights; in my spare time, I bring complex data to life through interactive visualizations and open tools—below is an overview of my skill set, and you can find out more in my blogs and projects.
Scientific Programming
R, Python, C++. Package development, data analysis, visualization, simulation.
Machine Learning / AI
Machine learning, deep learning, neural networks, with PyTorch, Sklearn, and more.
Modeling and Inference
Combining stochastic processes, graph theory, and network science
Big Data
Learning to use SQL, Spark, and other modern frameworks.
Web Development
HTML, CSS, JavaScript, interactive data visualization with D3.js.
GIS, Bioinformatics
Geospatial analysis, phylogeny reconstruction, metagenomics
Bash, Server, HPC
Server-side software maintenance, HPC management.
Scientific Writing
Typesetting, rendering and visualization with LaTeX, TikZ and PGFPlots.
Featured Blog Posts
HerdLink: Exploring NL livestock trade as a network
Livestock trade data looks nicer with dashboarding. This post introduces HerdLink—an interactive NL livestock trade network explorer ...
Sub-Species Level Diversification and Tree Coarsening
Diversification is an event-by-event process, and a tree can hide what actually happened. This post walks through a toy simulator turning “tree-like” history into a network ...
A Protocol to Bridge Phylogeny and GCN
Phylogenies are essentially graphs. Therefore, we can utilize a specific class of neural networks-the graph convolutional networks-to extract valuable information. But how? ...