About Me

I am a computational physicist (Ph.D.) with 10+ years writing scientific code, running computational experiments, and validating models against data. I currently evaluate frontier language models on expert-level physics reasoning and build neural-network surrogates of expensive simulations. I am the author of open-source scientific libraries (Paramo, Tleco; ApJ 2024) with code review and unit testing, and a mentor of graduate students. 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

• Scientific machine learning & surrogate modeling
• Computational modeling, simulation & HPC
• Language-model evaluation (scientific reasoning)
• Geospatial analysis & terrain modeling
• Data analysis & visualization
• Scientific communication

Resume

• Resume (PDF)
• Full CV (PDF)

Education

• Ph.D. in Physics — Universitat de València, Spain (Jul 2017, Excellent Cum Laude). Advisors: Prof. Miguel A. Aloy & Dr. Petar Mimica. Thesis
• M.Sc. in Physics — Universidad Michoacana de San Nicolás de Hidalgo, Mexico (Sep 2011). Advisor: Prof. José A. Cervera
• B.Sc. in Physics — Universidad Autónoma del Estado de México, Mexico (Dec 2008). Advisor: Prof. Francisco S. Guzmán

Professional Experience

Independent Contractor — Mercor (Jan 2026 – Present)

• Physics subject-matter expert evaluating frontier language models for multiple leading AI labs.
• Review 50+ expert-level physics, hydrodynamics, astrophysics, and cosmology problems; write original prompts that stump frontier models and diagnose failure modes in their reasoning.

Spatial Data Scientist — TealWaters (May 2025 – Jan 2026)

• Built geospatial ML pipelines and optimized terrain-analysis code for wetland mapping.
• Optimized the terrain-modeling code that computes elevation derivatives from 1 m, 3 m, and 10 m DEMs over 20 tiles, improving its computational performance.
• Mapped wetland probability across the 2,160 km² Skykomish watershed with the Wetland Intrinsic Potential (WIP) random-forest model, reaching >75% accuracy.

Independent Researcher & Open-Source Developer — Self-directed (Jan 2024 – May 2025)

• Co-developed Tleco, a Rust/Python toolkit that solves the Fokker–Planck equation coupled to radiative transfer to model radiation from relativistic outflows (ApJ 2024).
• Developing WindsOfChange with the UW Forest Mycobiome Lab: a C++/R library that simulates wind-driven spore dispersal over forested, hilly terrain, parallelized with RcppParallel and OpenMP.

Software Engineer — Paychex (Apr 2022 – Jan 2024)

• Built and tested data-integration services between enterprise systems and Oracle E-Business Suite.
• Developed and tested production data-pipeline software (Java, Python, SQL) with CI/CD.

Postdoctoral Research Associate — Rochester Institute of Technology (Feb 2021 – Apr 2022)

• HPC simulations of supermassive black hole binaries in an NSF-funded project.
• Led a 7-person team upgrading PatchworkMHD, a C code for MHD simulations of supermassive black hole binaries; added black hole spin with under 5% runtime overhead.
• Ran and benchmarked large production simulations on Frontera (TACC), about 10,000 node-hours, and identified performance bottlenecks in the parallel code.
• Calibrated Paramo against Fermi-LAT gamma-ray spectra with gradient-based optimization that updates the model automatically; supervised a graduate student on the same problem.
• Co-authored 2 papers from a multi-institution study of binary neutron star mergers.

Postdoctoral Research Fellow — Purdue University (Oct 2018 – Nov 2020)

• Radiative-transfer modeling of relativistic jets (blazars and gamma-ray burst afterglows).
• Designed and wrote Paramo, an open-source Fortran 95 library that solves the Fokker–Planck equation for relativistic particle distributions coupled to radiative transfer; optimized it with OpenMP and tested GPU offload with OpenACC.
• Implemented implicit PDE solvers, numerical integration, and arbitrary-shape particle distributions without slowing the simulation.
• Wrote Python tools to analyze Paramo output and run parameter optimization; other groups have adopted Paramo, including Combi & Siegel (2023).
• Served as Co-I on two NASA Fermi Guest Investigator grant proposals, one funded ($68K) to model blazar radiation; mentored 3 graduate students and published 2 peer-reviewed papers.

Postdoctoral Research Fellow — Universidad Michoacana de San Nicolás de Hidalgo (Jan – Sep 2018)

• Developed a Python pipeline to process black hole simulation outputs from the GRTrans numerical code, generating SVM training data for radio image prediction.
• Built open-source data analysis and visualization tools in Python for radiative transfer phenomena in relativistic astrophysics scenarios.

Graduate Research Assistant — Universitat de València (Oct 2011 – Jul 2017)

• Studied how magnetization of shocked plasma shapes the radiation spectra of relativistic internal shocks, using the C-SPEV simulation code.

Technical Skills

• Languages: Python, C/C++, R, Rust, SQL, Fortran 95, Java, Julia, Shell
• ML & Data: Scientific machine learning, language-model evaluation, surrogate modeling, Bayesian inference, Gaussian process regression, PyTorch, scikit-learn, TensorFlow, random forest, neural networks, SVM, gradient-based optimization, ML-assisted parameter estimation, NumPy, SciPy, Pandas, Astropy
• Geospatial: Sentinel-1/2 multispectral processing, DEM terrain analysis, raster/vector data pipelines, QGIS
• HPC & Parallel: OpenMP, OpenACC (GPU offloading), MPI, SLURM, PBS, HDF5
• Tools: Git, Docker, Azure, Jenkins, OpenShift, Kafka, Splunk, Jira, ParaView, VisIt

Publications

Selected (9 published articles, 3 first-author; 3 in preparation):

• 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
• Davis, Z., Rueda-Becerril, J.M., Giannios, D. (2022). “Balancing turbulent heating with radiative cooling in blazars”. Monthly Notices of the Royal Astronomical Society, 513(4), 5766-5779. DOI:10.1093/mnras/stac1282
• 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
• Guzmán, F.S., Rueda-Becerril, J.M. (2009). “Spherical boson stars as black hole mimickers”. Physical Review D, 80, 084023. DOI:10.1103/PhysRevD.80.084023

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 (talks and teaching in Spanish)
• English: full professional proficiency
• Catalan: basic knowledge
• Nahuatl: basic knowledge

Contact

• Email
• LinkedIn
• ResearchGate
• GitHub
• ORCID

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