Research

Trustworthy Decentralized AI

Trustworthy decentralized AI, with an emphasis on security, verifiability, and adversarial resilience in decentralized and multi-agent systems. Current work focuses on authenticated storage, trusted hardware, and verifiable decentralized infrastructure as foundations for trustworthy AI.

My research focuses on trustworthy decentralized AI, particularly security, verifiability, and adversarial resilience in decentralized and multi-agent systems. I am interested in how AI systems can operate reliably when participants, infrastructure providers, or agents may be faulty, compromised, or mutually untrusted. My current work on authenticated storage, trusted hardware, and decentralized infrastructure provides the systems foundation for this broader research direction.

Research Interests

Trustworthy decentralized AI

Secure and trustworthy decentralized systems

Privacy-preserving and verifiable computation

Current Research

These projects develop integrity, provenance, and fault-resilience mechanisms that can support trustworthy decentralized AI systems.

HiDCE

A trusted-hardware-assisted decentralized storage architecture that combines erasure coding, cryptographic verification, self-audit, and self-repair under partially trusted infrastructure.

Under review