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Report abuseEngineering educator and researcher building transparent computational tools.
I work at the intersection of scientific computing, AI/ML, thermal systems, digital twins, experimental design, and statistical quality. My public projects turn engineering questions into small, testable and inspectable software—so assumptions, data quality and evidence remain visible.
| Engineering question | Public work | What it demonstrates |
|---|---|---|
| Is the process stable and capable? | SPC Connect | X̄-R charts, capability analysis and downloadable audit records |
| Is the thermal behavior understandable? | Thermal Digital Twin | Simulation, synthetic observations, parameter fitting and error metrics |
| Is the input data ready for SPC? | Engineering Data Quality | Non-destructive validation, profiling and missingness reporting |
| How does a body cool or heat? | Heat and Mass Transfer Models | Lumped-capacitance equations, Biot checks and inverse calculations |
| Which factors should we study? | Engineering Experiment Design | Full-factorial designs, coded effects and physical-level decoding |
| What compute backend is actually available? | Scientific Computing ROCm | Conservative CPU/CUDA/ROCm detection and reproducible runtime metadata; includes a separate draft 2D PINN experiment |
I am developing a connected engineering-computation workflow:
design the experiment → validate the measurements → model the system → quantify error → document the runtime.
The emphasis is evidence over decoration: public repositories include focused APIs, unit tests and continuous integration where appropriate. Accelerator support is reported only when the local runtime exposes it; no hardware result is implied by a project name.
- Scientific machine learning and AI-assisted engineering
- Thermal modeling and digital twins
- Reproducible Python for engineering education
- Design of experiments and process improvement
- Statistical process control and engineering data analysis
- Portable CPU/CUDA/ROCm workflows
- Affiliation: Universidad Paraguayo Alemana (UPA)
- Location: Paraguay
- ORCID: 0009-0004-6275-3013
- Credential: Credly digital credential
Repositories · ORCID · Credly
Open to thoughtful collaboration around engineering computation, scientific ML, thermal systems and reproducible technical education.
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