The work visualizes and simulates the artist’s shifting weight across time, asking whether lived events shape the body’s form, or whether form itself shapes experience. Built from social media images spanning years, the artist constructs a 3D digital twin using a weight-estimation model that generates hybrid synthetic data. Through this process, personal history becomes material for a real-time exploration of the body as both archive and projection.
Archival photographs of the artist are processed through a deep-learning height and weight estimation model, producing a longitudinal dataset derived from images captured across different moments of life. Rather than treating these predictions as fixed measurements, the system preserves their variability, allowing inconsistencies caused by pose, clothing, and photographic context to remain part of the data. The resulting values are recorded over time, forming a synthetic trace of bodily change.
This dataset is then ingested into a real-time visualization pipeline. Weight values are parsed in TouchDesigner and transmitted via OSC to Blender, where Geometry Nodes deform a 3D body model through blendshape interpolation. Blender’s EEVEE engine renders the evolving form in real time and streams it back to TouchDesigner via NDI, where an interface situates the body within a temporal scale of age and weight.
The Body as a Form Through Time (2025) treats the body not as a stable biological constant, but as an evolving medium shaped by memory, technology, and interpretation. The work positions biometric data as a speculative material—one that reflects how identity is continuously reconstructed through time.
