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erickmuroz/README.md

Erick Muro Zaldívar

Engineering Science (B.Sc.) at the Technical University of Munich, finishing 2026. I work at the intersection of numerical methods, probabilistic inference, and computational finance. My current focus is Bayesian inverse problems: dimensionality reduction via Likelihood-Informed Subspaces and Gaussian-process surrogate modeling, applied to local-volatility calibration.

Looking for quantitative research / quantitative engineering roles and a Master's in Applied Mathematics or Mathematical Finance.

Current work

  • Bachelor's thesis — Bayesian Inverse Problems with Dimensionality Reduction Engineering Risk Analysis Group, TU Munich. Likelihood-Informed Subspace (Spantini et al., 2015) combined with Gaussian-process surrogates, validated on Black-Scholes local-volatility calibration: recovering a latent volatility field from noisy option prices through a linearized parabolic-PDE forward operator. → LIS-Bayesian-Inverse-Problems

Technical background

Numerical PDEs (finite differences / finite elements), Bayesian inference and uncertainty quantification, surrogate modeling, optimization.

Languages & tools: Python (NumPy / SciPy), MATLAB, R, SQL, C, Git, LaTeX

Spoken: Spanish (native) · German (C1) · English (C1)

Contact

erickmuroz@gmail.com · Munich, Germany

Pinned Loading

  1. MacCormack-FD-Counterflow-Heat-Exchanger MacCormack-FD-Counterflow-Heat-Exchanger Public

    MacCormack predictor-corrector scheme for coupled unsteady convection-diffusion equations, applied to a 1D counterflow heat exchanger. CTFD final project, TU München.

    Jupyter Notebook

  2. Combining-Dimensionality-Reduction--LIS-with-Surrogate-Modeling-GP- Combining-Dimensionality-Reduction--LIS-with-Surrogate-Modeling-GP- Public

    LIS (Likelihood-Informed Subspace) dimensionality reduction combined with a Gaussian-process surrogate for a linear Bayesian inverse problem on a 1D structural bar.

    MATLAB