Research and System Design
CORGData research connects assisted reproductive technology, clinical outcome modeling, population simulation, genetic-pool governance, and biological systems intelligence.
The work is organized around one central question:
How can biological outcomes be modeled before irreversible clinical, reproductive, or population-level decisions are made?
A short concept video on how CORGData connects biological data, predictive modeling, and governed system design.
Prefer listening? Audio version below.
Publications
Selected peer-reviewed publications in clinical outcomes, assisted reproductive systems, and predictive modeling.
Public Research Outputs
Blockchain Applications in Healthcare: A Review of the Health Data Exchange Landscape
Concept Papers
Genetic Pool Governance Framework
CORGData - Genetic Pools as Substrates for Investigating Latent Human Aptitude Architecture
CORGData - A Computational Model for Controlled Reproductive Selection at Population Scale
CORGData - A Governance and Ethics Framework for Computational Reproductive Selection Modeling
CORGData - An Open Methods and Data Description for a Governed Synthetic Genetic Pool Simulated with msp
rime
Biological Systems Modeling
Models and simulation outputs
CORGData uses model outputs to test assumptions, compare scenarios, and visualize biological system behavior.
Examples include:
predictive ART outcome models
age-dependent probability surfaces
synthetic cohort simulations
population-level distribution shifts
genetic-pool scenario modeling
diversity and selection-pressure tradeoff curves
CORGData research operates at the intersection of clinical data, computational modeling, and biological systems design.