From Code to Canvas: My Artistic Journey

As a software engineer, I’ve always been captivated by the elegance of algorithms and their ability to solve complex problems. But it was my fascination with evolutionary algorithms—systems that mimic the process of biological evolution—that opened up an entirely new realm of possibilities for me. The idea that a computer could "evolve" solutions, gradually refining them without explicit instructions, felt like magic. It wasn’t long before I wondered: Could this process be applied to art? Could algorithms evolve not just solutions, but beautiful, abstract images?

This question became my guiding obsession, leading me on a path to merge two of my passions—technology and art. During my time as a Master’s student at the University of Waterloo, I began developing algorithms that could generate complex mathematical functions. Through this process, I found a way to render those functions as images, evolving them just as nature evolves life. My goal was simple but ambitious: to create abstract art that was not designed by hand, but by the natural, unpredictable beauty of mathematics and computation.

The Art of Evolution: My Creative Process

At the heart of my work is a unique process that combines mathematics, evolutionary algorithms, and artistic intuition. I create mathematical functions that generate the color of each pixel in an image, representing these functions as genes, alleles, and chromosomes. Using a custom-built evolutionary framework, I generate populations of abstract images, each with its own genetic structure.

Much like in nature, the images evolve over time. I select the ones that resonate with me, then use the framework to mutate individual images or cross over two images to produce new, "child" images. This process continues, refining each generation until I’ve crafted a collection of abstract art that feels alive—rich with the complexity and depth that only evolution can create. Each image is not just a creation but a product of countless iterations, mutations, and the surprising beauty that comes from randomness and refinement.

A New Kind of Expression

What makes my art truly unique is not just the blend of technology and creativity, but the way each piece evolves. Every image I create is a result of carefully crafted mathematical functions and an evolutionary process that mirrors the unpredictability of nature. I don’t dictate the final form—instead, I guide it, shaping a space where art can emerge organically. Each collection represents an ongoing dialogue between the precision of algorithms and the expressive possibilities of abstract art.

My work is always evolving, just like the images themselves. I am constantly experimenting with new combinations of mathematical functions to create entirely new styles, exploring the endless possibilities of this intersection between art and technology. For me, the magic lies in this process of discovery—watching as shapes, colors, and patterns emerge from the code to create something that feels both calculated and completely alive.

How My Process Differs from Generative AI Art

In an era where AI-generated art is becoming more common, my process stands apart. While generative AI often relies on pre-trained models and vast datasets to produce images, my artwork is built from the ground up using evolutionary algorithms and mathematical functions. I don’t feed the computer examples of art to mimic; instead, I design mathematical expressions that dictate every pixel of the image. This means that each piece is born from the intrinsic logic of mathematics, shaped through an evolutionary process that I guide and curate.

Generative art as a concept is not entirely new. Pioneers like Karl Sims and Scott Draves were instrumental in the early exploration of computer-generated images, and today, the field continues to grow, with over 600,000 posts under the hashtag #generativeart on Instagram. My work builds on this tradition while taking a distinct path. Instead of relying on learned patterns, my art evolves organically, reflecting both the randomness and selection that mirrors natural processes.

The result is a collection of abstract works that are as unique and evolving as the algorithms that created them.