Systems researcher pursuing deterministic homeostatic and homeoadaptive architectures through adversarial validation and empirical refinement.

For the last 3 decades, I’ve been doing one thing consistently:
Exploration

I'm interested in:

• deterministic behavior
• inspectable systems
• tools that explain themselves
• automation that gives people their time back
• co-evolutionary systems
• cognition & recursive systems design

In 1999, with almost no formal programming background, I taught myself just enough Perl, Bash, and regex over a weekend to automate a manually intensive workflow. Hours were compressed into seconds. My peers and I got our days back.

I was hooked.

I love solutions!

• Verified compositional neural nets Systems where small, correct parts compose into larger systems with inherited correctness.

• Deterministic message-passing architectures Observable, replayable coordination of neural nets — not opaque execution.

• Learning as manufacturing Train → freeze → verify → deploy.
  ML as an engineering discipline, not a guessing game.

• TriX — A 2-Bit Conditional Ternary Neural Architecture with Learned Computational Sparsity and Emergent Routing
• Fungible Computation — Demonstrating Equivalence Between Neural and Classical Computation Through Exact Digital Emulation
• FLYNNCONCEIVABLE — Verified neural implementation of the 6502 CPU
• Hollywood Squares OS — A distributed micro-kernel designed for addressable processor networks where message passing serves as the fundamental syscall interface.

Focus: 0-Trust Neural Nets

I’m interested in collaborating on projects involving:

• systems architecture
• distributed computation
• verification
• automation
• unconventional ML approaches
• “this shouldn’t work, but it does”

If you’re building something thoughtful and a little weird, I’m listening.

• LinkedIn

• 💬 Open to DMs and collaboration

I have no idea what I am doing, but I know I am doing it really well. ✨