PÉTER LODRI
SOTA AI Systems Architect · Technical AI Safety · Quantitative Systems Researcher
Budapest / Remote (Global Nomad) • cabotage@pm.me • peterl.dev • axiomquant.org • github.com/peterlodri-sec • @0xp3t3rl.bsky.social

Target Focus & Profile Summary

Independent AI researcher and systems architect specializing in empirical multi-agent verification, mathematical AI safety bounds, and low-bit neural consensus distillation. Proven track record of architecting zero-reward-hacking evaluation harnesses, deriving exact geometric-mean consensus equivalences, and deploying low-latency edge models with formal spectral guarantees. Deeply aligned with Coefficient Giving's mission to address catastrophic risks from transformative AI through rigorous epistemic foundations, open-source verification tools, and pragmatic systems engineering.

Selected Research & Open Systems Contributions

KOMPRESS v2: Geometric-Mean Consensus Distillation & Spectral Rigidity
Lead Author & Architect · kompress.vaked.dev/paper/main_v2.pdf · HF Model
DeepSiper Enthea: Worktree-Isolated Multi-Agent Safety & AST Verifier
Principal Architect · github.com/8b-is/deepsiper-enthea
Axiom Quant: Pure Mathematics, Random Matrices & Stochastic Process Substrate
Founding Researcher · axiomquant.org · 86 Monographs
EtherHive & Honest-IRC: Sovereign Post-Quantum Cryptographic Messaging
Lead Cryptographic Engineer · etherhive.vaked.dev · github.com/peterlodri-sec/etherhive

Technical Core Competencies

AI Safety & Eval:
Multi-agent worktree harnesses, AST invariant validation, reward-hacking prevention, mechanistic interpretability, empirical incident deconstruction, free-theorem verification.
Modeling & Distill:
Geometric-mean logit consensus, teacher council ensembles, BitNet b1.58 ternary quantization ($\{-1, 0, +1\}$), PyTorch, MLX (Apple Silicon Metal kernels), Hugging Face Hub.
Mathematics:
Random matrix theory (Marchenko-Pastur, Tracy-Widom), stochastic calculus, spectral graph theory, Hawkes processes, Reynolds parametricity, category-theoretic semantics.
Systems & Infra:
Rust (async, zero-copy, SIMD, no-GIL), Python 3.13 JIT, TypeScript, Cloudflare Workers/Durable Objects, Kademlia DHT, Git worktrees, Linux eBPF/memfd.

Education & Philosophical Foundations

Self-Directed Higher Studies in Applied Mathematics & Computer Science
Deep study in random matrix theory, stochastic differential equations, abstract algebra, and category theory. Epistemic focus on Cartesian skepticism, falsifiability (Popper/Lakatos), and the causal coupling of artificial cognition to physical substrates.