Skip to main content

The Research Pipeline

A 30-month publication strategy: 6 papers across diverse journals, building academic authority toward PhD application. Starting from evidence. Building in public.

In Development

P1Beyond the Spectrum: A Case for Dimensional Profiling

Type: Perspective
Journal: Frontiers in Psychiatry
Timeline: Months 1–3

Critiques the linear spectrum model and introduces the case for dimensional profiling of autistic cognition.

Key areas:

  • Historical analysis of the autism spectrum model
  • Neuroscientific basis for dimensional approach
  • Preliminary DAI framework introduction
Research Phase

P2AI Detection of Autism: Systematic Review

Type: Systematic Review
Journal: Lancet Digital Health
Timeline: Months 3–6

Comprehensive review of AI and machine learning approaches to autism detection, with accuracy metrics and clinical implications.

Key areas:

  • 91.8% sensitivity in multimodal neuroimaging detection
  • EEG deep learning AUC 0.937
  • Eye-tracking accuracy ~88%
Research Phase

P3The DAI Framework: A Conceptual Model

Type: Conceptual
Journal: Molecular Autism
Timeline: Months 6–10

Detailed specification of the Dimensional Autism Intelligence model: the 8 axes, their neurobiological basis, and measurement approaches.

Key areas:

  • 8 independent cognitive axes
  • Neurobiological foundation for each dimension
  • Measurement and profiling methodology
Research Phase

P4A Century of Medical Failures in Autism

Type: Critical Review
Journal: Disability & Rehabilitation
Timeline: Months 8–12

Historical and critical analysis of medical and psychiatric approaches to autism — from refrigerator mother theory to modern overmedication.

Key areas:

  • Historical harm documentation
  • Critique of current treatment paradigms
  • Alternative frameworks for support
Planning

P5Autistic Cognition in the AI Workplace

Type: Perspective
Journal: Frontiers in Psychology
Timeline: Months 12–18

Explores how the 8-axis DAI model helps explain autistic cognitive strengths in technical fields and how AI teams can leverage these strengths.

Key areas:

  • Pattern recognition and systems thinking
  • Workplace environment optimization
  • Recruitment and retention strategies
Planning

P6Empirical DAI Pilot Study

Type: Empirical
Journal: Nature Mental Health
Timeline: Months 18–30

First empirical validation of the DAI framework using neuroimaging and cognitive profiling. Requires institutional affiliation (secured via visiting researcher route by Month 18).

Key areas:

  • Neuroimaging validation (fMRI, DTI, sMRI)
  • Cognitive testing battery
  • Clinical and non-clinical cohorts

Publication Strategy

This 30-month pipeline is designed to build academic authority and citation history before PhD application. Papers 1–5 require no lab access — they are literature reviews, perspectives, and conceptual work based on published research. Paper 6 requires institutional affiliation, which will be secured via a visiting researcher position by Month 18.

Each paper is written with full citations, peer-reviewed rigor, and input from the 15-agent collaborative team. Every claim is evidence-backed. Nothing is speculation.

The Science Behind This Timeline

2025 Stanford study: The fastest-evolving neurons in the human brain (L2/3 IT neurons) are the same neurons where autism-linked genes concentrate. This is the foundation of the entire project. AI detection now achieves 91.8% sensitivity in multimodal neuroimaging. The tools exist. The evidence is there. The framework just needs to catch up.