About Kenneth Mendoza
Kenneth Mendoza is a computational researcher and inventor with 30+ years of experience in substrate optimization and information-theoretic modeling. His work spans molecular biology, materials science, quantum computing, and AI systems.
Background & Education
UCLA (circa 1990) - Double major in Molecular Biology and Political Science, with specialized training in Philosophy of Science and epistemology. This unique interdisciplinary foundation enabled Ken's breakthrough approach to computational substrate mapping.
Career Highlights
1996 - Digital Lava (Co-Founder, NASDAQ) - Pioneered computational substrate optimization during TIMSS educational research, establishing the theoretical foundations for HS(ρ)Lang three decades before formal patent filing.
2005-2007 - Arbor Vita Corporation - Computational modeling work became foundational for NA-1/Nerinetide, a stroke neuroprotection drug that achieved:
- $90 million in investment
- Phase III clinical trials with 1,105 patients across 48 hospitals globally
- Published in The Lancet (February 2020) - 19% more patients recovered, 50% mortality risk reduction
2010-2025 - Professional Photographer - 15 years at San Francisco City Hall, photographing 10,000+ weddings. Notably photographed Perplexity CEO Aravind Srinivas's wedding, establishing personal connection relevant to current AI interpretability partnership discussions.
2025 - Oregon Coast AI LLC - Formal launch of H²-LANG patent portfolio with partner Toni Bailey, targeting commercial applications across immunology, materials science, cybersecurity, and AI safety.
Key Achievements
Current Research
The HS(ρ)Lang (H²-LANG) Framework represents Ken's life work: a universal computational substrate mapping system grounded in Koopman-von Neumann mechanics (1931), Shannon entropy (1948), and information-theoretic foundations. Applications span:
- Immunology (H²h) - Immune system modeling with 87% accuracy
- Materials Science (H²m) - Phase transition prediction with quantum validation
- AI Safety (H²ai) - LLM interpretability and alignment verification
- Cybersecurity (H²c) - Intrusion detection with 1,013× speedup
- Deepfake Detection (H²df) - Boolean substrate authentication
Patent Portfolio Access Tiers
Public
Open access to abstracts and validation highlights
- Patent abstracts
- Validation summaries
- Business contact info
NDA-Gated
Technical specifications after NDA signature
- Detailed specifications
- Claims analysis
- Licensing frameworks
- Requires signed NDA
Full Access
Complete patent suite with approval
- Complete patents
- Source code
- Validation data
- Requires approval