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Advanced Visualizations of Complex Data

Since 2012, I've been fascinated by the power of clear, effective visuals, whether untangling complex ML model outputs or illustrating simple data stories.

Principles in my Work

Code-first, Psychological Knowledge, Vision Science, Graph Accessibility, Grammar of Graphics, Graphic Design

Read more about these principles

You'll find my visualizations are code-first, which means they're agile and ready to update as the data evolves. I bring my cognitive science domain knowledge to this - understanding what makes a graph work for people based on evidence on how we read visuals (like research by Garcia-Retamero et al, 2017) and making sure they're accessible (color-blind friendly, Birch, 2012).

My approach leans on strong quantitative data design fundamentals: the grammar of graphics (Wilkinson, 2005) and is informed by elegant graphic-design principles, like informative grid layouts.

Why all this effort? Because well-crafted visuals are key to understanding complexity.

Examples of my Data Visualizations

Sparse Bayesian Model
of Covid-19 Digital Health
Vaccination Decision
Features in 26'700 People
Properties of
World Democracies in 2020
view code view code view code
Major Depression
Symptoms on 52 Clinical Scales
ISO Country Codes
Fried (2016) publication view code

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Data visualizations, information design, quantitative graphic design

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