Structure that emerges from chaos.
vortex collapse visualisations
attractor trajectories (Halvorsen, Rössler)
phase-space flow fields
transport pathways in nonlinear systems
where mathematics becomes something you can watch unfold.
System resilience.
tipping point surfaces under parameter drift
resilience decay under sustained perturbation
stochastic forcing effects on equilibrium structure
early-warning signal visualisations
Not predictions - structure of risk itself.
Mapping coherence.
deal flow networks
startup ecosystem maps
founder relationship graphs
investment scoring landscapes
Not “which company wins”, but “where signal begins to concentrate.”
Structured data, live & direct.
choreography visualisation (Babylon.js)
animation driven by structured datasets
synchronised audio-visual systems
performance-optimised rendering pipelines
where datasets become experiences.
What is being carried.
Koopman mode decompositions as spatial patterns
spectral signatures of evolving systems
coherent structures extracted from noisy trajectories
latent flow fields from observed data
seeing order in what initially looks like noise.
Finding deals that can go the distance.
startup discovery pathways
filtering layers from raw data to shortlisted deals
relationship structures between founders and sectors
signal propagation across datasets
carefully mapping investment pipelines:
Systems that can't stay stable forever.
state-space landscapes
basin transitions
probability flow visualisations
regime boundary identification
where systems prefer to sit - and what forces them to leave.
Exploring dynamics.
Directly.
simulation environments for chaotic systems
interactive phase-space explorers
data-driven visual dashboards
real-time system evolution models
not a report - A laboratory.
Systems breakdown too.
simulations showing numerical instability emergence
collapse scenarios under parameter extremes
bifurcation-induced sudden behavioural change
robustness testing across stochastic regimes
where models stop behaving and start revealing their assumptions.
Exploration through mixed media.
photography (travel, urban systems, structure in environments)
music production
experimental visual/audio work
“systems thinking” applied visually rather than mathematically.
Complex ideas, readable by humans.
annotated simulations with layered explanations
stepwise unfolding of system behaviour over time
comparative “before vs after structure extraction” views
minimal diagrams explaining high-dimensional processes
Bridging between understanding and intuition.
Who can juggle CEO, CFO and CTO.
behavioural clustering patterns
progression trajectories
network influence effects
signal amplification over time