I design and maintain governed, deterministic AI–human research systems focused on transparent, reproducible, and falsifiable science.

My work centers on three connected layers of the Aurora research ecosystem:

• ARI — Aurora Research Initiative, the institutional governance and metadata framework that defines epistemic legitimacy
• AWO — Aurora Workflow Orchestration, the formal methodology for governed AI–human research
• CRI-CORE — the deterministic execution and constraint-enforcement runtime that implements AWO’s rules

These frameworks provide the backbone for open-science case studies, including Waveframe v4.0 (cosmology) and the Societal Health Simulator (SHS) (applied systems-science modeling).

I treat reproducibility and governance as first-class research objects, not afterthoughts.

Practical commitments:

• Replayability: Any published result should be re-runnable from code + metadata alone.
• Determinism: Given the same inputs and environment, workflows should converge to the same artifacts.
• Provenance: Every artifact must carry an auditable trail of decisions, versions, and model interactions.
• Governance before trust: If a process cannot be governed and constrained, its outputs are not scientifically trustworthy.

If research cannot be replayed, audited, and verified — it doesn’t count.

The Aurora stack is intentionally layered: governance → method → runtime → case studies.

        ┌─────────────────────────────────────────────┐
        │ ARI — Aurora Research Initiative            │
        │ Governance, policy, and metadata standards  │
        └───────────────────────────────┬─────────────┘
                                        │
        ┌───────────────────────────────┴─────────────┐
        │ AWO — Aurora Workflow Orchestration         │
        │ Formal method for governed AI–human flows   │
        └───────────────────────────────┬─────────────┘
                                        │
        ┌───────────────────────────────┴─────────────┐
        │ CRI-CORE — Execution & Enforcement Runtime  │
        │ Deterministic runs, constraints, integrity  │
        └───────────────────────────────┬─────────────┘
                                        │
        ┌───────────────────────────────┴─────────────┐
        │ Case Studies / Applied Systems              │
        │ Waveframe v4.0 • Societal Health Simulator  │
        └─────────────────────────────────────────────┘  

Institutional governance and metadata framework for reproducible AI–human research.
🔗 https://github.com/Waveframe-Labs/Aurora-Research-Initiative
Concept DOI: 10.5281/zenodo.17743096

Formal methodology for transparent, governed, human-in-the-loop research workflows.
🔗 https://github.com/Waveframe-Labs/Aurora-Workflow-Orchestration
Concept DOI: 10.5281/zenodo.17013612

Deterministic execution and constraint-enforcement engine implementing AWO rules.
🔗 https://github.com/Waveframe-Labs/CRI-CORE

Cosmology case study demonstrating governed reproducibility in scientific modeling.
🔗 https://github.com/Waveframe-Labs/Waveframe-v4.0
Concept DOI: 10.5281/zenodo.16872199

Applied systems-science reproducibility testbed for sociotechnical modeling.
🔗 https://github.com/Waveframe-Labs/Societal-Health-Simulator
Concept DOI: 10.5281/zenodo.17258419

• governed AI–human research workflows
• provenance and metadata architectures
• institutional research governance
• reproducible computational science
• model auditing and verification
• applied cosmology and systems modeling

📧 swright@waveframelabs.org
🌐 https://waveframelabs.org
🧭 ORCID: https://orcid.org/0009-0006-6043-9295