
landscape
generative art
01:05
2025
Seph Li (born 1988, Beijing) is a Chinese media artist based in London whose practice explores interactive systems at the intersection of technology, perception, and natural phenomena. Working with real-time computation, he develops poetic, rule-based environments in which dynamic processes such as fluid behavior, flocking systems, and physics-based simulations become the foundation for abstract visual forms. Within these systems, the artist defines the underlying structure, while the resulting imagery is co-created through algorithmic processes and audience interaction, producing works that evolve continuously in response to both code and presence.
Seph Li holds bachelor’s degrees in Computer Science and Digital Design from Tsinghua University and an MFA from the Design|Media Arts department at UCLA. His work has been exhibited internationally in major museums and institutions, where his installations extend beyond static display into participatory experiences that engage viewers directly in the formation of the artwork.

Excerpt from a real-time interactive artwork
In the forest, between freely growing trees, a phenomenon called 'crown shyness' naturally occurs: the tree crowns don't overlap, forming channel-like openings. Like human crowds, trees in the forest automatically find their own place. Competing for light, they ultimately find balance through cooperation and maintain their own position.
The title comes from a Chinese idiom - 'If trees were old like this, how can humans survive it?' (树犹如此,人何以堪). Originally, it expresses a lament for the swift passage of time; in this work, it extends to the relationship of competition and cooperation that trees can naturally form, while humans often lose this far-sighted ability in our fast-paced society.
The custom software implements a complex tree growth algorithm that drives real-time light simulations. Trees seek areas of greater light and gradually form crown shyness patterns. An AI-based tracking system is also used, removing the need for heavy stereo cameras or expensive LiDAR devices.
generative art
landscape
01:05
2025