Emmanuel Antonio Diaz Gutierrez

Developed Python-based learning modules for Finite Element (FE) Data Generation and Design of Experiments (DoE) for optimization algorithms applied to computational mechanics. Implemented Surrogate-based Optimization using Genetic Algorithms and Neural Networks (GNN).

Constructed test models in 3DEXPERIENCE Motion and performed complex Multi-Body Simulation (MBS) focusing on longitudinal dynamics. Developed a Graph Neural Network (GNN) for automatic model detection and classification. Systematically tested and documented tutorials for the 3DX Motion App.

Applied the finite element method (FEM) using ANSA, Hyperworks, NASTRAN, and Ls-Dyna to evaluate complex load paths and ensure structural integrity across the entire vehicle development process. Correlated simulation models with physical testing to validate compliance with FMVSS (207/210/208) and ECE (R14/17) regulations, applying strong analytical skills to assess structural accelerations and occupant safety metrics.

Generated complex FE models (meshing, material assignment) and defined the seatbelt routing/anchorage scenarios for Dummy interactions in LS-DYNA. Optimized the CAE process chain by standardizing reporting methodologies, effectively communicating design improvements and subsequent development steps to cross-functional international teams. Implemented Design of Experiments (DoE) workflows using Siemens HEEDS to identify optimal design variables and optimization of final design.

Led end-to-end design (CAD), simulation (CAE), and manufacture of the battery accumulator and modules of the electric racing car UM-E4 for Formula Student.

Graduated with merit. Relevant coursework in Linear and non-linear Finite Element Analysis, Explicit FEM, Risk Analysis, Structural Dynamics, Car Body Design, Advanced Fluid Dynamics, Computational Linear Algebra, Artificial Intelligence, and Machine Learning. Master’s Thesis: A Generic Framework for Simulation-based Surrogate Modeling and Machine Learning.

Graduated with honors. Final thesis "Mechanical Design of the Battery System for the Formula SAE vehicle UM-E4 2021". Degree in mechanical engineering with a specialization in mechanical design, where I took relevant courses in Algebra, Integral and Differential Calculus, Differential Equations, Modeling of physical systems, Statistics, Probability, Mechanics of Materials, Design of machinery elements, Thermodynamics, Fluid Dynamics, Computer-Aided Design & NVH fundamentals for design.