Building at the intersection of physics, machine learning, and real-world systems.
I'm a researcher and engineer who likes taking ideas all the way down — from the math and physics, through the model, to hardware and shipped software. My work spans physics-informed machine learning, quantum dynamics, network security, and geospatial systems. I care about rigor and about things that actually run in the field.
| Project | What it is |
|---|---|
| quantum-ml-pinn | Physics-informed neural approaches to quantum dynamics — solving the time-dependent Schrödinger equation and studying where learned solvers meet classical integration. |
| math-physics-notes | Self-study courses & notes: proof techniques, groups & Lie theory, and variational methods for intelligent systems. |
| tufutfem-mx | A web platform for Mexican women's football (Liga MX Femenil) — hardened Node/Express backend behind Caddy. |
| cluster-guide | A practical guide to building a 3-node home compute cluster. |
Also working privately on LiDAR volumetric scanning (geospatial), routing/QoS ops for logistics, cadastral valuation ML, and a Raspberry Pi network-security node.
Neuromorphic Engineering · Physics-informed ML · quantum computing · statistical physics (KPZ, percolation, random fields) · IDS/network security · LiDAR & computer vision · edge computing.
“From the equations to the field.”