Posts by Collection

portfolio

Super Resolution on cosmology

Published:

Computational physics and cosmology super resolution research project developed at UNAM, Social Service project Cosmología Observacional a través del Cómputo Científico

Proyecto de investigación en física computacional y super-resolución cosmológica desarrollado en la UNAM, Servicio Social Cosmología Observacional a través del Cómputo Científico

Scattnet-MR

Published:

Interpretable machine learning framework for accelerated MRI reconstruction based on wavelet scattering transforms. Currently under review at Computers in Biology and Medicine.

Framework de machine learning interpretable para reconstrucción acelerada de MRI basado en transformadas de scattering wavelet. Actualmente en revisión en Computers in Biology and Medicine.

Smart Docs

Published:

Intelligent document processing powered by LLMs and OCR — extract structured data from documents using modern AI pipelines.

Procesamiento inteligente de documentos con LLMs y OCR: extrae datos estructurados de documentos usando pipelines modernos de IA.

SRGAN in Astrophotography

Published:

Processing and Enhancement of Planetary Astrophotography Using Generative Adversarial Networks

Procesamiento y mejora de astrofotografía planetaria usando redes generativas antagónicas

publications

Scattnet-MR: Interpretable Machine Learning for Accelerated MRI Reconstruction

Published in Computers in Biology and Medicine (under review), 2026

Interpretable MRI reconstruction using wavelet scattering transforms and neural implicit representations.

Reconstrucción interpretable de MRI usando transformadas de scattering wavelet y representaciones neuronales implícitas.

Recommended citation: Villalba, D. (2026). "Scattnet-MR: Interpretable Machine Learning for Accelerated MRI Reconstruction." Computers in Biology and Medicine. Under review.
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resources

Research Internships & Academic Profile Resources

Published:

This page compiles the primary resources discussed in the seminar:
“Cosmología sin fronteras: ¿Cómo conseguir una estancia internacional de investigación y no morir en el intento?” (Seminario Estudiantil de Física – Facultad de Ciencias, UNAM).

This page compiles the primary resources discussed in the seminar:
“Cosmología sin fronteras: ¿Cómo conseguir una estancia internacional de investigación y no morir en el intento?” (Seminario Estudiantil de Física – Facultad de Ciencias, UNAM).

talks

teaching

Propedeutic Courses Science Faculty

Workshop, Universidad Nacional Autónoma de México, Facultad de Ciencias, 2015

As part of the Propedutic Courses at the Faculty of Sciences, I had the opportunity to teach Analytical Geometry, a fundamental subject aimed at helping incoming students bridge the gap between high school and university-level mathematics. These preparatory courses were designed to provide students with a solid foundation in key mathematical concepts, ensuring they could confidently tackle the rigorous coursework of their first semester.

As part of the Propedutic Courses at the Faculty of Sciences, I had the opportunity to teach Analytical Geometry, a fundamental subject aimed at helping incoming students bridge the gap between high school and university-level mathematics. These preparatory courses were designed to provide students with a solid foundation in key mathematical concepts, ensuring they could confidently tackle the rigorous coursework of their first semester.

Almacenes y Minería de Datos (2026-2) — FC-UNAM

Undergraduate course, Facultad de Ciencias, Universidad Nacional Autónoma de México (UNAM), 2026

Undergraduate course focused on the design and implementation of modern analytical data systems, integrating dimensional modeling (Kimball), ETL/ELT processes, data quality, and core concepts of data mining. The course emphasizes a unified view of the data lifecycle, from data ingestion and transformation to analysis and modeling, through reproducible examples in Python and materials developed with Quarto.

Undergraduate course focused on the design and implementation of modern analytical data systems, integrating dimensional modeling (Kimball), ETL/ELT processes, data quality, and core concepts of data mining. The course emphasizes a unified view of the data lifecycle, from data ingestion and transformation to analysis and modeling, through reproducible examples in Python and materials developed with Quarto.