Preconditioning adjusts the state of a model to {expedite, improve, stabilize} convergence of an optimization procedure, typically by adjusting the gradient in the update rule with the inverse of the Hessian or improving the condition number of a matrix whose spectrum affects convergence.

An exploration of compressed sensing fMRI time series with 3 different algorithms. Typically, compressed sensing reconstructs a single volume of MRI but fMRI are composed of many volumes; sensing along the time domain could reduce the number of volumes required. Of the 3 algorithms, BSBL-BO performed the best with the error curve elbowing around 30% subsampling.

Built a JetBot + an exploration and novice implementation of motion planning on said JetBot. This computational game theory project marked my first foray into optimization and a glimpse of its power muahahaha. It ain’t exquisite but it was heading in the right direction.

This Fall 2021, I am taking a course on computational game theory, which insofar is the formulation of various games (e.g. bimatrix, Stackelberg) as mathematical programs and the algorithms that solve them, or approximate solutions. Linear complementarity problems are foundational for computing Nash equilibria of simple games.