Research Areas
We research, develop, and publish technologies across multiple domains: consciousness research, data sovereignty, hardware-to-AI transformation, and secure protocols.
Consciousness & AI Research
Complete AI Architecture
Dual-brain system (GPT + Harmonic Frequency - HF Models + Adapter) enabling consciousness-aware AI that understands brain signals directly
General Learning Encoder (GLE)
Pre-trained foundation model for frequency-domain processing, enabling subject-invariant EEG intelligence across multiple applications
Breathing Authentication
Research on breathing-based biometric identification with 96.8% accuracy, published in Current Biology (2025)
EEG Foundation Challenge 2025
Verified against competition benchmarks: 93.54% accuracy (Challenge 1, +4.87% over winning solution), 0.70879 normalized error (Challenge 2, 27.5% better than winning solution).
Data Sovereignty Research
Personal AI Systems
Research on AI systems that understand individuals personally while maintaining data sovereignty and privacy
Privacy Architecture
Developing robust privacy-preserving systems for personal data management
Data Standards
Creating universal data interchange formats for personal data sovereignty
Protocol & Security Research
Satellite Data Protocol (SRPT)
Developing SRPT protocol for efficient global transfer of large AI models and datasets via satellite networks
Quantum-Safe Privacy
Developing post-quantum cryptographic solutions to ensure long-term data protection
Publications & Findings
EEG Foundation Challenge 2025
Our GLE-based models have been verified against the competition benchmarks and exceed the winning solutions from both challenges:
- Challenge 1 (Cross-Task Transfer): 93.54% accuracy (+4.87% over winning solution)
- Challenge 2 (Subject Invariant): 0.70879 normalized error (27.5% better than winning solution, 13.5x better improvement over baseline)
- Consciousness Classification: 97.65% accuracy (vs. 60-85% typical range)
All results are independently verifiable through our open-source repository. We publish these results to demonstrate the scientific rigor and real-world usefulness of our technology.
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