Art and science provide alternate frameworks for understanding the natural world. My work is increasingly motivated by the pursuit of realism at the intersection of these disciplines. I’ve written several articles exploring connections between painting, color science, image processing, and photography. I weave all this research into my paintings using an ever-expanding constellation of computer programs.

Low-Cost Visible Light Spectral Imaging, 2021

Journal of the International Colour Association


Spectral power distributions are an informationally-complete, observer-independent measurement of light & color. These are typically measured with expensive hyperspectral cameras. I developed a method at less than ten percent the cost, fusing and reconstructing measurements from optimally sparse samples using commodity hardware.

Visualizing Color Space in 2D, 2020

We perceive color in three dimensions - red, green, blue. By analogy of mapmaking, visualizing higher-order information in two dimensions can improve its tractability. I developed a "color map" to provide persistent awareness of position within color space, so that it can be navigated, learned, and utilized more effectively by color practitioners.

Paint Palette to Color Gamut, 2020

As a follow-up to How Paints Mix, I developed a method for calculating an exhaustive set of recipes or "cookbook" for any given set of primary paint colors. This enables direct translation between a set of paints and its corresponding digital color gamut, and rapid color decomposition by lookup.

Oil Painting Color Calibration, 2020

I developed a simple, effective method for accurately color-calibrating photos of oil paintings. It uses black/white neutral paint mixes to automatically set both levels and white balance.

3D Focal Point Median Blur, 2020

Whereas cameras have a focal plane, human vision has a focal point. To bridge this gap, I developed a method for variably de-focusing stereoscopic images in 3D space around a desired focal point to better simulate a single moment of human vision.

How Paints Mix, 2019

The color wheel is a popular tool for teaching the basics of color mixing. However, it offers no explanation for why its predictions should be true, nor does it generalize across the color gamut. I developed a mathematical model of color mixing in oil paints, characterizing the spectral absorption and scattering of light within the paint film. This enables predicting the color of any paint mixture, and decomposing any color into a mixing recipe.