19 Patents Across Proteomics & Cross-Domain Innovation
From drug target identification to quantum error correction—a journey of discovery that bridges biology and physics through universal mathematical principles.
All sharing a common mathematical foundation: hysteresis-based stability control derived from immune system dynamics.
Multi-threshold, dwell-time hysteresis applied to quantum syndrome detection, reducing false corrections through biologically-inspired stability mechanisms.
Hysteresis-based frameworks for preventing oscillation and improving convergence in artificial intelligence optimization systems.
Applying immune-inspired threshold dynamics to climate monitoring and detection systems for improved signal-to-noise discrimination.
Stability control mechanisms adapted for music and audio analysis, enabling more robust pattern recognition in complex acoustic signals.
Enhanced quantum sensing applications through hysteresis-based noise filtering and stability control mechanisms.
Ken's quantum computing work focuses on hardware-based methods that reduce false syndrome triggers and stabilize quantum systems. By applying multi-threshold hysteresis originally derived from immune system dynamics, these approaches address one of quantum computing's fundamental challenges: distinguishing real errors from measurement noise.
The methods are designed for compatibility with existing quantum hardware architectures and have been validated on IBM Quantum platforms using native Qiskit implementations.
Thermodynamic AI optimization reduces hallucination, improves interpretability, and enables efficient music and audio models. By treating neural networks as thermodynamic systems, these methods identify and eliminate high-entropy states that lead to unreliable outputs.
Extensions to music analysis and generative media leverage the same entropy-based framework to detect structure, predict next-note probabilities, and generate coherent audio sequences.
Fast phase prediction for materials and solid-state batteries achieves 107–108 speedups versus traditional simulation methods. Information-theoretic approaches predict phase transitions and battery failure modes by analyzing entropy signatures rather than running computationally expensive molecular dynamics.
Early warning systems for battery thermal runaway and dendrite formation provide advance notice of failure, enabling safety interventions before catastrophic events.
Geophysical inversion and spatial analysis frameworks enable climate risk assessment, subsurface imaging, and environmental monitoring. These methods detect anomalies and predict tipping points by analyzing entropy gradients across spatial and temporal domains.
Applications range from earthquake early warning to climate pattern detection and hydrological modeling.
Quantum-era security and sensing architectures use hysteresis and entropy to stabilize and protect quantum networks. These methods address vulnerabilities unique to quantum systems, including decoherence-based attacks and eavesdropping on quantum communication channels.
Emerging quantum sensing architectures are designed for deployment and validation on platforms like IBM Quantum, with extensions to quantum network security and quantum key distribution.
Computational, Danger Theory–inspired models estimate immune state, monitor autoimmune conditions, predict cancer immunotherapy outcomes, and provide early warning for mental health deterioration through neuromorphic psychoneuroimmunology frameworks.
These models detect danger signals in biological systems—stress markers, inflammatory cascades, and neuroimmune interactions—to provide context-aware health monitoring that goes beyond traditional biomarker analysis.
Biomimetic apoptosis defense and deepfake detection via entropy inversion provide security for critical infrastructure and media validation. Just as cells undergo programmed death when compromised, these systems detect and isolate compromised components before they spread damage.
Deepfake detection methods analyze entropy signatures to distinguish authentic from synthetic media, providing real-time validation for video, audio, and image content.
| Domain | Problem | Solution |
|---|---|---|
| Immune System | Prevent premature immune activation | Multi-threshold hysteresis → reduces autoimmunity |
| Quantum Computing | Prevent false syndrome detection | Dwell-time hysteresis → reduces false corrections |
| AI Systems | Prevent optimization oscillation | Stability control → improves convergence |
| Climate Detection | Distinguish signal from noise | Threshold dynamics → better detection |
This cross-domain insight wouldn't have emerged from staying within traditional disciplinary boundaries. Sometimes the best solution to a physics problem comes from biology. If you're working on stability problems in noisy systems—whether biological, quantum, or AI—the answer might be hiding in a completely different field.
Co-inventor on foundational proteomics patents
Novel approaches to identifying and validating therapeutic targets
Computational biology methods for molecular structure analysis
LIMS architecture for research data management
Therapeutic approaches for stroke treatment
Whether you're exploring licensing opportunities, research partnerships, or technology transfer, let's discuss how this universal framework might apply to your domain.