Independent researcher and computer science educator working across nonlinear systems, mathematical AI, machine learning, and reproducible computation.

Research site · ORCID · LinkedIn

• Nonseparability characterizes SONC exactness for interior signed supports

  An analytic characterization of SONC exactness, with exact and interval-certified computation for the explicit witness and quantitative benchmark.

• Averaged-Jacobian failure at the first open width of the Neural Jacobian Conjecture

  A certified separation between pointwise Jacobian positivity and the averaged-Jacobian mechanism at planar width four. The global behavior of the canonical witness is resolved in the follow-up below.

• Asymptotic-polygon global inversion for planar saturating ridge networks and an injective neural-Jacobian separation witness

  A global inversion theorem resolving the certified separation witness as an injective global diffeomorphism onto an explicit nonconvex octagon, with exact and validated parameter certificates.

• Ptolemy structure, sign rigidity, and pure-braid kernels in colored braid groupoid representations

  Exact structural identities, exhaustive sign-rule analysis, and rational inner pure-braid kernel computations along certified flip sequences.

Each research repository distinguishes analytic arguments from computational verification and links its principal claims to reproducible artifacts.

• AI Playgrounds — live site · source — twelve bilingual browser-based visualizations for search, logic, probability, machine learning, neural networks, vision, and reinforcement learning.
• RLVR and GRPO studies — compact studies of regularized policy-improvement operators and a CPU-scale GRPO reproduction.
• Engineering portfolio — projects across evaluation, retrieval, agents, machine learning, Rust systems, infrastructure, and security.

I prefer analytic structure where it is available, then exact algebra, interval arithmetic, certified computation, and independent reconstruction where finite computation carries claim weight.

Primary tools: Python, Rust, NumPy, SciPy, SymPy, TensorFlow/Keras, Hugging Face, and Terraform.

Open to research collaboration, technical review, and roles in mathematical AI, machine learning, and research engineering.