About Me
I am a computational scientist with a Ph.D. in Physics and 10+ years developing high-performance numerical algorithms and physics-based simulation software. My expertise spans multiscale/multiphysics modeling, scientific computing, and scientific machine learning, with a track record of publishing peer-reviewed research, obtaining competitive grants, and collaborating across interdisciplinary teams to solve complex computational problems in physics. Growing up in the highlands of central Mexico, I developed a deep appreciation for natural landscapes, which continues to fuel my applied research in environmental and physical systems.
Selected Skills
- Data science & machine learning
- Computational modeling & simulation
- Data analysis & visualization
- Geospatial analysis
- Scientific communication
Resume
Education
- Ph.D. in Physics — Universitat de València, Spain (2017, Cum Laude). Advisors: Prof. Miguel A. Aloy & Dr. Petar Mimica. Thesis
- M.Sc. in Physics — Universidad Michoacana de San Nicolás de Hidalgo, Mexico (2011)
- B.Sc. in Physics — Universidad Autónoma del Estado de México, Mexico (2009)
Professional Experience
Independent Contractor - Mercor (Jan 2026 — Present)
- Provide expert-level knowledge in Physics, Astrophysics, and Mathematics to improve models for top AI research labs.
- Assess model reasoning quality, identify failure modes, and provide structured feedback to improve scientific accuracy.
- Apply understanding of mathematical foundations to benchmark model performance on complex STEM problems.
Spatial Data Scientist — Tealwaters, Seattle, WA, USA (May 2025 - Jan 2026)
- Lead the development and refinement of tools like the Wetland Intrinsic Potential (WIP) model, integrating geomorphic and hydrologic indicators to map wetlands.
- Apply remote sensing and geospatial analysis to ecological modeling, focusing on wetland restoration and environmental impact.
- Bridge astrophysics and environmental science by leveraging expertise in high-performance computing, statistical modeling, and machine learning to analyze complex environmental datasets.
Open-Source Developer — Independent Research (Jan 2024 - May 2025)
Tleco- Simulates relativistic plasma particles and radiation rise from accelerating particles.
- Combines Rust and Python functions from the Fortran code
Paramo.
WindsOfChange- Simulate spore dispersion in hilly terrains using R and C++.
Software Engineer — Paychex (Apr 2022 - Jan 2024)
- Developed and maintained internal tools using Java, Python, and SQL.
- Collaborated with cross-functional teams to automate workflows and improve data pipelines.
Postdoctoral Research Associate — Rochester Institute of Technology (Feb 2021 - Apr 2022)
- Modeled particle acceleration and high-energy radiation in relativistic outflows using the Fortran code
Paramo. - Investigated plasma processes such as magnetic reconnection, shocks, and turbulence.
- Simulated supermassive black hole binaries, accretion disk dynamics, and jet formation using Harm3D and PatchworkMHD.
Postdoctoral Research Fellow — Purdue University (Oct 2018 - Nov 2020)
- Developed
Paramo, an open-source Fortran 95/OpenMP code for radiative transfer simulations in relativistic astrophysics. - Served as Co-Investigator on two NASA Fermi Guest Investigator Program proposals (one awarded), advancing the understanding of physical constraints shared by the two main blazar types.
- Built Python tools for numerical energy-loss and spectral-evolution calculations in gamma-ray burst afterglow modeling.
- Collaborated with a multidisciplinary team to model the COVID-19 outbreak in Mexico and produced public science communication for Spanish-speaking audiences.
Postdoctoral Research Fellow — Universidad Michoacana de San Nicolás de Hidalgo (Jan - Sep 2018)
- Built a Python pipeline to process 2D simulation images from the
GRTranscode and generate training data for an SVM classifier predicting black hole spin from radio image morphology. - Developed an open-source Python tool for calculating radiative transfer phenomena (spectra and light curves) in relativistic astrophysics.
- Organized a workshop training graduate students in the HDF5 data storage format.
Technical Skills
- Programming Languages: Python, C/C++, R, Fortran, Shell, Julia, SQL, Rust, Java
- Python Ecosystem: Numpy, Pandas, Matplotlib, Scipy, Astropy, Scikit-learn, Tensorflow, PyTorch, Pytest, Jupyter
- Miscellaneous: Git (GitHub, Bitbucket), $\LaTeX$, QGIS, MPI, OpenMP, OpenACC, HDF5, Mathematica, Maple, Docker, Jenkins, Splunk, Jira, Kafka, MongoDB, Visit, Paraview, Job Scheduling (SLURM, PBS)
Publications
Selected:
- Davis, Z., Rueda-Becerril, J.M., Giannios, D. (2024). “Tleco: A Toolkit for Modeling Radiative Signatures from Relativistic Outflows”. The Astrophysical Journal, 976(2), 182. DOI:10.3847/1538-4357/ad8bc2
- Rueda-Becerril, J.M., Harrison, A.O., Giannios, D. (2021). “Blazar jets launched with similar energy per baryon, independently of their power”. Monthly Notices of the Royal Astronomical Society, 501(3), 4092-4102. DOI:10.1093/mnras/staa3925
- Rueda-Becerril, J.M., Mimica, P., Aloy, M.A. (2017). “On the influence of a hybrid thermal-non-thermal distribution in the internal shocks model for blazars”. Monthly Notices of the Royal Astronomical Society, 468(2), 1169-1182. DOI:10.1093/mnras/stx476
Full list: ADS · arXiv · Google Scholar
Personal Interests
Beyond astrophysics, science, the environment, and computers, I love hiking and climbing mountains.
Languages
- Spanish: native proficiency
- English: full professional proficiency
- Nahuatl: basic knowledge
- Catalan: basic knowledge