Pierre CasadebaigRidge Regression

Ridge Regression is a tour of imagined landscapes rooted in data visualization, drawing from real elevation logs that reveal the landscape topography of France's diverse mountain ranges.

The project’s algorithm involves an evolutionary process applied to geology, where new plausible landscapes are built by recombining a set of randomly sampled real location(s).

Because the data does not convey human influences on the land, the resulting landscapes are stripped to their basic, raw forms. By observing the differences between real locations and these fragments of computational geological forms, the artworks highlight the impacts we have on our world – from inspiring transformations to consequential damages.

While some outputs contained unremarkable elements, their potential as components for broader compositions was harnessed by assembling them with stronger outputs, leading to the creation of those synthetic yet realistic landscapes. The project goes on to harmonize additional algorithmic systems for additional ridges, writings, and clouds – using a responsive grid layout that adapts to the shape of generated components.

Lastly, to give these bare forms and natural expressions further life, the algorithmic drawings were output in pen-plotter renderings that embrace an organic feel through coding techniques like line overlays and noise, and also by using physical brushes, calligraphic pens, and technical pens. Through these processes, the works are open to serving as intimate, elevated celebrations of imagined natural forms, or as exploratory gestures to be traded and sent as mementos of peaks not yet climbed.


Pierre Casadebaig

Pierreis is a biologist and computer artist based in France. With a background in using code and data visualisation to analyse crop-environment interactions, Pierreis' practice shifted in 2020. He began applying these analytical techniques to his artistic ideas, resulting in a distinctive body of monochrome line art. By altering real or generated datasets through data science methods, he creates...
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TENDER is a leading curatorial platform and practice for contemporary generative art, growing a new breed of gallery. Aiming to advance generative art as a medium, core practices include artist collaborations, collector activations, and in-person experiences of digital creations. Innovations across these disciplines increasingly show a broader audience what generative (computational, algorithmic...
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