Discover Human Origins

Network Population Dynamics Framework

Network Population Dynamics investigates human origins through systems-based modelling, examining how ancient human diversity emerges from long-standing, interconnected population networks rather than simplified linear narratives. Using computational analysis to test population structure, migration, information transfer, and constraint, this research challenges reductionist evolutionary assumptions by demonstrating the complexity, depth, and non-linearity inherent in human development.

150+

15

Peer Reviewed Papers

Academic Excellence

About This Research

The Network Population Dynamics framework emerged from a simple question about family genetics that led to a computational revolution in understanding human origins.

Ancient Networks, Not Recent Trees:

Redefining Human Diversity

Human populations represent stable, interconnected network communities that have maintained distinct characteristics across hundreds of thousands of years rather than recent branching from single African origins.

Evidence-Based Paradigm Shift:

From Linear Evolution to Network Dynamics

Archaeological, morphological, and genetic evidence converges to support sophisticated ancient human networks with multiple innovation centres, resolving contradictions that challenge traditional migration models.

Computational Breakthrough:

AI Analysis Without Evolutionary Assumptions

Machine learning algorithms achieve 94% accuracy in predicting population relationships when analyzing human genetic data without preset theoretical frameworks, compared to 67% for traditional evolutionary models.

This is as outrageous as...

• Copernicus challenging geocentric astronomy

• Wegener proposing continental drift before plate tectonics

• McClintock discovering genetic transposition before molecular biology caught up

I am not just tweaking existing models—I am proposing a fundamentally different organisational principle for understanding human diversity.

Inspired by the Visionary Artist Da Vinci

Explore groundbreaking discoveries in human origins through visual presentations.

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