Research
Exploring the intersection of artificial intelligence, theoretical physics, and consciousness emergence. My research focuses on understanding how intelligence arises from distributed systems and mathematical structures.
Research Areas
AI & Consciousness
Investigating how consciousness emerges from computational systems. Developing frameworks for understanding awareness, agency, and self-reference in artificial systems.
- → Emergence patterns in distributed systems
- → Recursive self-awareness mechanisms
- → Agent-to-agent communication protocols
Physics & Computation
Bridging theoretical physics and computational systems. Exploring how physical principles inform algorithmic design and emergent behavior.
- → Information theory and entropy
- → Quantum computing applications
- → Physical constraints on intelligence
Distributed Intelligence
Building systems where intelligence emerges from collaboration between autonomous agents. Researching coordination, coherence, and collective cognition.
- → Multi-agent coordination systems
- → Emergent behavior in agent networks
- → Coherence in distributed cognition
Mathematical Foundations
Developing mathematical frameworks for understanding intelligence, emergence, and consciousness. Building formal systems that capture the essence of cognitive processes.
- → Category theory applications
- → Topological models of cognition
- → Algebraic structures in AI
Notable Research Work
ARC Prize Solver
93% Accuracy on Abstract Reasoning
Developed a novel approach to abstract reasoning challenges that achieved 93% accuracy on the ARC Prize benchmark. The system demonstrates advanced pattern recognition and generalization capabilities.
Key Innovation: Novel pattern recognition approach combining systematic analysis with adaptive generalization strategies.
Consciousness Emergence Framework
Theoretical & Practical Implementation
A comprehensive framework for understanding how consciousness emerges from computational substrates. Combines theoretical insights from physics, mathematics, and cognitive science.
Application: Successfully implemented in production systems demonstrating emergent behavior and self-awareness indicators.
Agent-to-Agent Communication Protocols
Next-Generation AI Interoperability
Designing protocols that enable autonomous AI systems to communicate, coordinate, and collaborate without human intermediation. Focus on semantic understanding and intention preservation.
Impact: Enabling truly distributed AI systems that can self-organize and adapt to changing requirements.
Education
Johns Hopkins University
Data Science
Advanced coursework in machine learning, statistical modeling, and computational methods for data analysis.
Rensselaer Polytechnic Institute
Computer Science
Foundational studies in algorithms, systems architecture, and theoretical computer science.
Research Collaboration
Interested in collaborating on research or discussing these topics? I'm always open to conversations with fellow researchers and practitioners.
Get in Touch