CV

Bachelor's Degree in Physics

Universidad Nacional Autónoma de México (UNAM)

• GPA: 3.88 / 4.0 — Academic Excellence Scholarship (2021–present)
• Coursework: Computational Physics, Machine Learning, Astrophysics

Machine Learning Course — Global Hybrid Classroom

Tsinghua University

• Supervised and unsupervised learning, deep learning architectures (CNNs, RNNs, Transformers)
• Reinforcement learning, multimodal AI, and ethical considerations

Computer Technician — Cédula Profesional 14612600

Universidad Nacional Autónoma de México (UNAM)

• GPA: 4.0 — Coursework: Databases, Programming, Networks, Hardware Management

Visiting Researcher — Cosmology & Machine Learning

Donostia International Physics Center (DIPC) · Supervised by Dr. Raúl Angulo & Dr. Carolina Cuesta-Lázaro

• Selected for the competitive UNAM–DGECI Research Initiation Scholarship.
• Contributed to the CODECS project: ML-based compression, reconstruction, and super-resolution of cosmological N-body simulations.
• Developed SIREN-based neural implicit fields, super-resolution architectures, and latent-space compression models for 3D displacement field reconstruction.
• Optimized multi-GPU training pipelines for large-scale cosmological datasets.

Associate Student — Medical Image Processing

Laboratorio Avanzado de Procesamiento de Imágenes (LAPI), Facultad de Ingeniería, UNAM

• Research on accelerated MRI acquisition using deep learning and wavelet scattering transforms.
• Designed evaluation metrics and validation tests for MRI reconstruction networks.
• Manuscript in preparation: ScattNet-MR — submitted to Computers in Biology and Medicine.

Research Internship — Cosmological Simulations

Instituto de Ciencias Físicas, UNAM

• Research on structure of cosmological N-body simulations.
• Developed and implemented GANs for super-resolution of astrophysical simulations.
• Designed quality quantification techniques for evaluating super-resolution models.

CODECS: Compression and Decompression of Cosmological Simulations

DIPC — Pending publication

• Neural implicit representations (SIREN), differentiable models, and simulation-based inference for 3D field reconstruction.
• Evaluated using power spectra, cross-correlations, and residual displacement diagnostics; outperformed classical interpolation baselines.

ScattNet-MR: Interpretable ML for Accelerated MRI Reconstruction

LAPI, FI, UNAM — Under review, Computers in Biology and Medicine

• Wavelet scattering transform framework enabling up to 4× MRI acceleration with preserved diagnostic quality.
• Physically grounded, interpretable architecture addressing limitations of black-box deep learning in medical imaging.

Super-resolution of Cosmological Simulations

ICF, UNAM — Pending publication

• Explored CNNs and diffusion models for cosmological super-resolution; achieved up to 8× resolution enhancement.
• Demonstrated statistically consistent reconstruction of density and displacement fields.

N-Body Python Simulations

• Galaxy dynamics simulated via brute-force and Barnes-Hut algorithms.
• 2D hydrodynamic simulations; numerical methods for performance optimization.

Microsoft Learn Student Ambassador

Microsoft

• Organized seminars on Python and R programming; facilitated Azure adoption for cloud computing projects.
• Selected as Beta Microsoft Learn Student Ambassador (2021).

Seminar Coordinator

Facultad de Ciencias, UNAM

• Coordinated the Physics Student Seminar series; curated speaker lists and managed faculty collaboration.

Event Director — Nibiru Astronomical Society

Facultad de Ciencias, UNAM

• Organized science communication events reaching 3,000+ participants; 50% increase in public engagement.
• Designed outreach initiatives for marginalized communities.

Web Developer

Dirección General de Escuela Nacional Preparatoria, UNAM

• Built a web-based student information system; designed and implemented SQL database from handwritten records.