Paper 'SEEK' received a Paper with Distinction award at IDETC-CIE 2025; Paper 'Operator learning with Gaussian processes' published in Computer Methods in Applied Mechanics and Engineering; Paper 'A gaussian process framework for solving forward and inverse problems involving nonlinear partial differential equations' published in Computational Mechanics; Successfully defended candidacy exam, PhD thesis titled 'Integrating Deep Learning with Gaussian Processes for Scientific Computing'.
Research Experience
Develops probabilistic machine learning methods to model complex systems across various scientific and engineering domains; Started a machine learning engineering internship at Patreon in June 2025.
Education
PhD: University of California, Irvine, Computational Science and Engineering; BSc: Polytechnic University of Catalonia, Aerospace Engineering (with honors).
Background
PhD candidate at the University of California, Irvine, specializing in computational science and engineering. Research interests include machine learning, data fusion, and uncertainty quantification.
Miscellany
Awarded the Balsells fellowship; Gave a talk on neural operators and Gaussian Processes for operator learning at the CRUNCH seminar.