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sunghunkwag/README.md

Independent AI Researcher

I design AI architectures through hypothesis-driven research. My repositories constitute an experimental portfolio testing foundational assumptions about scalable intelligence systems using AI-augmented conceptual modeling methodologies.

Contact: sunghunkwag@gmail.com

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  1. DHC-SSM-Enhanced DHC-SSM-Enhanced Public

    DHC-SSM v3.0: Production-ready Deterministic Hierarchical Causal State Space Model with O(n) complexity

    Python 1

  2. pegasus-project pegasus-project Public

    Advanced AI system research initiative exploring meta-cognitive bootstrapping and transcending human cognitive boundaries through epistemological exploration and recursive self-modification.

  3. SSM-MetaRL-TestCompute SSM-MetaRL-TestCompute Public

    Unified meta-reinforcement learning benchmark for fast adaptation with State Space Models (SSM), test-time improvement, and modular policy orchestration. Includes automated training, evaluation, ad…

    Python

  4. Autonomous-Self-Organizing-AI Autonomous-Self-Organizing-AI Public

    Autonomous Self-Organizing AI System: A reward-free, self-goal-setting architecture with high-order meta-cognition, intrinsic motivation, and emergent intelligence through information-theoretic pri…

    Python

  5. EFCA-ADAPT-Unified-Advanced-AI-Blueprint EFCA-ADAPT-Unified-Advanced-AI-Blueprint Public

    Unified EFCA-ADAPT Advanced AI System Architecture: Complete integration blueprint from neuromorphic hardware to recursive self-improvement, featuring EFCA-v2 cognitive architecture with production…

    Python

  6. gnn-codec-holography gnn-codec-holography Public

    Neural network compression research using GNN + holographic encoding. Experimental implementation exploring compression techniques.

    Python