Models with explicit assumptions
Use the structure a problem gives us. Track uncertainty and test where a representation succeeds, breaks down, or needs new evidence.
Our approach
Discovery is a loop.
Connect models to physical systems, learn from measurement, and use that evidence to choose what to build next.
The scientific loop
Each cycle informs the next.
Simulation and physical implementation work together. Results feed back into the model and the next experiment.
- 01Model
Define the question, assumptions, and system.
- 02Simulate
Explore behavior and compare candidate approaches.
- 03Build
Develop an implementation to investigate the question.
- 04Measure
Observe behavior and compare it with the prediction.
- 05Refine
Use what we learn to improve the next model and experiment.
Method
Make every result useful.
Meaningful comparisons
Compare methods under the same objectives, constraints, and evaluation budgets. Examine failure cases alongside improvements.
A reproducible record
Keep inputs, versions, runs, measurements, and analysis connected so the next experiment can build on what the last one taught us.
From method to evidence
Follow the work.
Our publications document the questions, methods, and results behind the research.