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Researcher in entropy, information, meaning, and language
🔗 ORCID: 0009-0001-0857-096X

Open Research Institute

I study how information, meaning, and language link physics to cognition. Information is physical; meaning emerges from geometric operations; language is the machinery that propagates meaning across scales—from atomic interactions to thought. My work maps this geometry, shows how the same patterns recur at every level, and ground the theory in physical evidence.

Link: https://osf.io/preprints/psyarxiv/4nv79_v1

How naming draws boundaries that discretize continuous reality, why that incompleteness drives paradox, and how it sets up the self-reference problem that links cognition to quantum measurement.

Link: https://doi.org/10.5281/zenodo.15715747

Meaning arises from a cycle of differentiation (A ≠ not-A) and integration (A = A across contexts). Shows why Gaussian structure is a geometric necessity and unifies linguistic processing across neurons, computers, and chemistry.

Link: https://doi.org/10.5281/zenodo.15898912

Self-referential meaning has one stable solution: three coupled verification systems at different timescales with constrained communication. The architecture reappears in neural, cellular, social, and cosmic systems—consciousness as stable self-representation.

Link: https://zenodo.org/records/17156438

Maps how patterns persist, decay, and emerge through integration, dissolution, and resonance-driven creation. Derives genuine novelty, 3+1 spacetime, and time's arrow from verification geometry.

Link: https://zenodo.org/records/17705796

Demonstrates the theory in matter: the hydrogen atom as the minimal three-state verification structure. Chemistry becomes linguistic communication governed by the same geometric constraints as human language.

Neural Entropy Analysis Pipeline
Peer-reviewed work (Brain Congress 2025, Brazil): computational pipeline for neural dynamics using information-theoretic measures. More detail coming soon.

• EM Fundamental Frequency — locating resonance points where interference generates new patterns; physics + data analysis of electromagnetic structure as linguistic interaction.
• Abiogenesis — modeling the transition from chemical communication to biological language; predicting required conditions for the phase change to life.
• Ethics, Alignment, and Human Behavior — applying the information architecture to coordination problems, moral intuitions, and AI alignment.
• Non-Hallucinating AI Systems — building AI with S1/S2/S3 hierarchical flow so coherence is structural rather than statistical.

• Psychology graduate student
• Full stack developer
• Published peer-reviewed neuroscience research
• Music Teacher