Data Science & Statistics
Rigorous inference over hype. Experimental design, causal modelling and statistics that survive contact with production data.
TIMONIELSENcreative technologist
01
What I do
One practice, two languages — mathematics and light. No decks. Working systems and finished frames.
ML & AI Architecture
End-to-end intelligence pipelines — from feature stores and training infrastructure to low-latency inference at the edge.
Photography & Film
A photographer’s eye applied to systems, and an engineer’s discipline applied to the frame. Stills, motion, colour.
Interactive Design
GPU-accelerated web experiences. Shaders, scroll choreography and typography treated as an engineering material.
02
Selected work
Systems in production, frames in print. Metrics are the aesthetic.
03
How I work
Three moves. No theatre.
01
Frame
Every system starts as a question. I scope the signal, the constraint and the audience before a single line ships.
02
Model
Statistics first, architecture second, aesthetics always. Prototypes become pipelines; moodboards become shaders.
03
Ship
Production is the medium. Observable, versioned, fast on a phone in the field — not just on a workstation.
04
Field notes
Stills between systems — 35mm, digital, latent.
05
Toolkit
- Python
- PyTorch
- TensorFlow
- scikit-learn
- Pandas
- SQL
- Spark
- Airflow
- dbt
- AWS
- Docker
- Kubernetes
- TypeScript
- Next.js
- React Three Fiber
- Three.js
- GLSL
- GSAP
- Figma
- Lightroom
- Capture One
- DaVinci Resolve
- Premiere Pro