Today my work centers on AI engineering, data science, and machine learning systems. That path began in scientific research: I studied physics at the University of The Andes, completed a master's in Complex Systems Modeling, and earned a PhD in Physics Applied to Medicine and Biology at the University of Sao Paulo before moving into applied AI and ML systems work.
How I work
- Define the problem carefully before reaching for models, prompts, or tooling.
- Keep pipelines reproducible so results can be trusted, debugged, and improved.
- Evaluate claims honestly instead of optimizing for the appearance of capability.
- Make systems understandable enough to trust, especially when the stakes are high.
At Carta Healthcare, I built ETL and NLP pipelines for clinical data, standardizing heterogeneous sources into HL7- and FHIR-compliant formats and integrating LLM-assisted extraction into registry workflows.
At TripleTen, I mentor learners through forecasting, classification, NLP, time series, and LLM projects with an emphasis on evaluation rigor, production-minded system design, and technical communication.
I am especially interested in work that sits between research depth and practical execution: machine learning systems, applied AI workflows, and technical communication that makes complex ideas genuinely usable.
I have authored 5 peer-reviewed publications in journals including Chaos and Chaos, Solitons & Fractals, focused on complex systems, nonlinear dynamics, and data-driven modeling. Browse selected publications or view Google Scholar .
