Advanced computational methods pointed at concrete engineering, industrial and public-sector problems — never at clean textbook data.
Foundations and applications of generative models: architectures, prompting and evaluation, fine-tuning, retrieval, and what it actually takes to put a model in front of real users without it falling over.
Theory and practice of visual communication: encodings that survive scrutiny, interaction that earns its complexity, and the discipline of building the one chart that has to change a decision.
Linear and logistic regression, principal component analysis and clustering, applied end to end on real industrial-engineering data.
I supervise theses at the Faculty of Engineering on generative AI and what it is doing to work, education and public argument. Write to me with what interests you, or ask what is open.
cnavarretel@udec.cl →