"Different minds resonate with different rhythms - let's map the spectrum"
Data Scientist | Cognitive Neuroscience PhD | Exploring Cognitive Architectures for AI
Living Portfolio | Portfolio v2.1
This is a dynamic research portfolio representing ongoing experimental work in AI interpretability and cognitive modeling. New tools and frameworks are added regularly as research progresses.
Initial Sprint: June-July 2025 (4 weeks) | Status: Actively developing
Latest Addition: AI Perceptual Signatures Study |
Currently Building: Cross-model resonance patterns
Throughout my work, I use terms like "neurotypical," "ASD," and "ADHD" as communication tools, not rigid categories. These labels describe tendencies, not destinies - they represent different valid ways of processing information, not deficits or disorders.
As I explain in my full disclaimer: "When I say 'ASD-TIDE,' I'm not talking about a disorder. I'm talking about a systematic, pattern-based approach to cognition that happens to align with patterns often seen in autistic individuals. It's a cognitive style that our world desperately needs."
The TIDE Philosophy: Cognitive patterns are dynamic, not fixed. Everyone uses different strategies in different contexts. The goal is understanding, not categorization.
Rutgers University
"The Neural Representation of Abstract Concepts in Typical and Atypical Cognition"
Explored how different cognitive architectures process abstract concepts using fMRI analysis.
Data Scientist - Consumer Packaged Goods
Leading data science initiatives across all divisions, creating enterprise-wide impact through:
4-Week Research Sprint
Created 12+ interactive research tools translating neuroscience insights into AI frameworks.
Building on years of PhD research, I rapidly prototyped these interactive tools in an intensive development sprint.
Ongoing Research & Development
Actively developing new tools and conducting AI perception research while maintaining corporate DS role.
Latest Addition: AI Perceptual Signatures Study
Currently Building: Cross-model resonance patterns
As a Data Scientist in CPG, I've driven strategic decision-making across all divisions through advanced analytics and innovative modeling approaches.
Generating unique data on how different AI models perceive complex systems
We're conducting the first systematic study of how different AI models perceive and describe the same complex visualization - revealing cognitive diversity in AI systems.
Mathematical foundations exploring neurodiversity as computational innovation
Temporal-Internal Dimensional Encoding
Mathematical framework mapping how different cognitive architectures organize self and time dimensions for equivalent outcomes.
Boundary Information Neural Dynamics
Information transformation at system boundaries with Φ (integrated information) measurement.
Integration of frameworks showing trust dynamics
Interactive exploration of how different cognitive architectures build trust through shared experiences.
First systematic study of AI cognitive diversity
Contribute to groundbreaking research on how different AI models perceive and describe complex systems.
Additional frameworks and experimental prototypes from the 4-week sprint (and ongoing)
Information Geometry Visualization
Information geometry visualization using optimal hexagonal packing structures for consciousness mapping.
Trust Evolution Models
Mathematical models of trust evolution, cooperation, and deception in multi-agent systems.
Discrete Information Processing
Discrete units of information as fundamental building blocks - exploring information quantization.
Computer Vision Experiments
Computer vision experiments using hexagonal grids for pattern recognition and visual processing.
Phase Transition Detection
Pattern detection algorithms for identifying phase transitions and overflow conditions in complex systems.
Meta-Repository Overview
Comprehensive overview connecting all frameworks into unified cognitive architecture research.
What appears as "deficit" may be efficient reorganization
Different architectures may build trust through different pathways
Each architecture potentially resonates with different environmental patterns
Diverse teams may outperform homogeneous ones
These insights reframe cognitive differences as architectural variations - like different operating systems that excel at different tasks.
"Different minds may achieve similar outcomes through different dimensional organizations of self and time. By exploring these patterns mathematically, we could build AI systems that leverage cognitive diversity for robustness, adaptability, and innovation."
Cognitive diversity isn't a bug - it's a feature for creating robust AI systems.
Rapid prototyping of interactive tools to explore theoretical frameworks.
Bridge neuroscience insights with AI development for interpretable systems.
Apply my tools to your models and explore cognitive diversity in AI systems
Extend frameworks together and contribute to the growing research ecosystem
Solve specific interpretability challenges using novel visualization approaches
Lead interpretability initiatives and bridge neuroscience with AI development
Interested in exploring how these experimental approaches might apply to your AI systems?
All frameworks and visualizations presented are experimental research tools designed to explore novel approaches to AI interpretability and cognitive modeling.
Remember: Labels are maps. Cognition is the territory. Let's explore it together.
Portfolio v2.1 | Living Document | Last Updated: