Summary
Ignacio Migliaro is a computational chemist and research associate with nine years of experience specializing in machine learning–driven design and automation for homogeneous catalysts and materials. He blends deep expertise in Python, cheminformatics (RDKit), ML (graph neural networks, active learning, deep learning), and high-performance computing to accelerate chemical space exploration and discovery. His work spans molecular dynamics, DFT, and machine-learned interatomic potentials applied to catalyst–polymer interactions, reaction mechanisms, and polymer recycling optimization. Ignacio has hands-on experience building automated workflows and cloud infrastructure for training ML force fields and applying them to crystal structure prediction for drug-like molecules. Comfortable collaborating with experimentalists, he translates computational insight into actionable strategies to improve catalytic performance. Based in Denton, Texas, he pairs rigorous academic training (PhD work at University of North Texas) with practical software and simulation engineering to push interdisciplinary boundaries.
9 years of coding experience
Bachelor's degree, Chemistry, Bachelor's degree, Chemistry at Universidad de Guanajuato
Doctor of Philosophy - PhD, Chemsitry, Doctor of Philosophy - PhD, Chemsitry at University of North Texas