Paolo Čerić

aka Patakk

Croatian

1990

Paolo Čerić is a computer scientist and visual artist whose work explores how simple algorithms can generate intricate, organic structures. Using custom tools built in Python, Processing, and Blender, he creates large-scale series that reveal the expressive potential of code.

Full Bio

Paolo Čerić, aka Patakk, was born in 1990 in Zagreb, Croatia, where he continues to live and work. He holds two master’s degrees from the Faculty of Electrical Engineering and Computing at the University of Zagreb and studied artificial intelligence at the Universidad Politécnica de Madrid through the Erasmus Programme. An entirely self-taught artist, his creative practice developed outside of formal education, shaped instead by trial and error, online tutorials, and long periods of independent exploration. He is trained as a computer scientist and works as a research engineer in the field of machine learning while maintaining an active artistic practice

Čerić is drawn to the contrast between the precision of code and the unpredictability of organic forms, often exploring how simple algorithms can give rise to complex, lifelike structures. He works with Python, Processing, Blender, and Cinema 4D, often writing his own tools to automate variation and enable large-scale iteration. His process balances engineering logic with visual intuition, allowing him to curate outputs through what he describes as a kind of visual editing. Among his most recognized bodies of work is the Single Stroke series, which renders human forms as continuous spirals of ink, inspired in part by classical sculpture.

His work has been shown in exhibitions including D-izložba in Zagreb and Perfekt Prints in Vienna. His early GIF animations were included in Moving the Still at Art Basel Miami, a group show co-curated by Michael Stipe of R.E.M. While still a student, he collaborated with the Zagreb Dance Center on  a series of interactive projections for live performance. In recent years, he has expanded his practice to include diffusion models, applying his technical background to explore new directions in algorithmic image-making.