News
2023
New preprint about learning hypergraph function structure from data using Gaussian Processes! - December 2023
My paper Kernel Methods are competitive for Operator Learning has been published in the Journal of Computational Physics (JCP) - November 2023
I passed my candidacy! Find the slides from my candidacy talk here - October 2023
My new preprint about constrained inference in inverse problems, including a disproof of the Burrus conjecture, is now out! Optimization-based frequentist confidence intervals for functionals in constrained inverse problems: Resolving the Burrus conjecture. Slides and a poster are available - October 2023
I gave a talk about my paper on kernel methods for operator learning at ICIAM 2023, in the "Machine Learning in infinite dimensions" minisymposium. Slides are available here - August 2023
I attended the Graduate Student Mathematical Modeling Camp (GSMMC) 2023 and the Mathematical Problems in Industry (MPI) Workshop. I worked on chaotic ODE modeling for wind speed prediction during the Camp and a Darcy Flow PDE source inversion problem during the workshop, in collaboration with Pacific Northwest National Lab (PNLL) - June 2023
New preprint available: Error Analysis of Kernel/GP Methods for Nonlinear and Parametric PDEs - May 2023
New preprint available: Kernel Methods are competitive for Operator Learning - April 2023
My paper in Multiclass classification utilising an estimated algorithmic probability prior has been accepted for publication in Physica D: Nonlinear phenomena - March 2023