Case Study
Feb 2026
Why 90% Accuracy is Often a Symptom of Model Failure
High AUC and accuracy metrics can mask structural flaws like temporal myopia or severe class imbalance. This breakdown explores how to use non-Gaussian null hypotheses to identify when a model is simply "memorising" noise rather than extracting signal.
Coming soon on Medium
Methodology
Drafting
Causal Discovery in Multi-Scale Time Series
Standard transfer entropy often fails on complex industrial sensor data. By using symbolic calculus and ordinal patterns, we can assess the directionality of information flow across multiple time scales simultaneously.
Expected publication: March 2026
Research
Scheduled
The Physics of Pathological Residuals
When residuals exhibit power laws or Lévy flights, Gaussian-based stress testing produces systematically wrong answers. A look into why "fat tails" are the primary source of predictive failure in high-stakes environments.