Inspired by Dutch artist Piet Mondrian. Made with an interest in color theory and a love for color in general.

Dot Grid

Invasion Percolation is the first network visualization of modern network science and the first generative network art. The algorithm was built by Albert-László Barabási in 1994, and the surviving 1995 output opened the Hidden Patterns retrospective of BarabásiLab at ZKM Karlsruhe in 2021 and the Ludwig Museum in Budapest in 2020. The release of Invasion Percolation as a generative NFT is part of a hybrid performance involving the metaverse and the traditional gallery and museum space. Each copy of the 782 series, corresponding to the number of links on the published 1995 version of the work, will be printed and each printed work’s title, permanently recorded on the physical artwork, will be the NFT owner who generates the work. In rare instances, the algorithm will generate sculptures that will be 3D printed. The 2D and 3D prints will be shown at the Cyberart Gallery in Boston, Postmaster Gallery in New York, Ludwig Museum in Budapest (Hungary), and New Kriterion Gallery in Csikszereda (Transylvania, Romania), each location receiving unique artworks. With the release of Invasion Percolation as a generative NFT, empty exhibition spaces will gradually fill in thanks to the actions of the collectors, who generate and name the work.

Invasion Percolation

Computation is one of the most powerful tools for our age. It opens up a whole world of possibilities. Some people use its power to solve the mysteries of our universe through science. I’m using it to explore our relationship with beauty and perception.

“Miragem” *(Mirage in Portuguese)* is a generative project that requires your slow attention. It’s an exploration of rhythm, balance, and texture. Just simple elements in a coordinated dance, ruled by math and randomness.

**It’s an invitation for the eyes and mind to wander.**


 >>  ‎  
>> ## “Beauty is the mystery of life. It is not in the eye, it is in my mind. In our minds there is awareness of perfection.”
>> Agnes Martin

 ‎
*Please check the project website to know more about the composition and features.*

Miragem

Initially worn by miners and cowboys, roughly half of the world’s population wears denim on a given day, and the range of styles is–literally–endless. A new pair of jeans might be acid bleached, sandblasted, stonewashed, or tie-dyed; it can have hand-sanded rips and tears, followed by visible mendings, patches, intentional paint stains, and more. In an epic attempt to crack the genetic code of denim, Jenim playfully but carefully observes and translates the warp and weft of denim into generative code, weaving unique iterations of irregular, distorted, or hyper-realistic textile crops.

Ironically, imitating aging, a pair of jeans produced today generates more pollution and labor than most average garments. In response, Jenim’s minted iterations go beyond wearables and into infinity. Each year that passes, the color might fade slightly; the rips might expand. Who knows what these artworks will look like ten or even fifty years from now?

Jenim

Space Birds begin with three simple polygon forms; triangles, quadrilaterals and pentagons. Combined and layered, they twist and morph their shapes as they rotate in space, mimicking the appearance of an unfolding bird-of-paradise flower while other objects orbit around them. Keyboard shortcuts: Hold the mouse button down to pause the animation. Type 's' or 'S' to save a screenshot. Drop Mechanic: Dutch Auction with a starting price of 2Ξ and price decreasing by 0.25Ξ every 5 minutes. 
Pricing Tiers: 2Ξ > 1.75Ξ > 1.5Ξ > 1.25Ξ > 1Ξ >0.75Ξ > 0.5Ξ > 0.25Ξ 

Twenty-five percent (25%) of the artist’s proceeds from the minting of Space Birds will be divided among the following charities: Alex’s Lemonade Stand Foundation for Childhood Cancer, The Leukemia & Lymphoma Society, Lymphoma Research Foundation, The International Waldenstrom’s Macroglobulinemia Foundation, and the Ellis Fischel Cancer Center at University of Missouri Hospital.

Art

Company

Learn