Research

Alternating Direction Method of Multipliers (ADMM) for nonconvex LQR optimization

With Professor Myung Cho at California State University, Northridge

Examined the theortical convergence of ADMM in a nonconvex setting applied to LQR control problems.

Implemented Python prototypes to examine convergence of ADMM-based algorithms in nonconvex environments and to confirm the theortical convergence using numerical simulations. Then developed the Python-relaed code in Matlab.

Fractal Uncertainty Principle (FUP) for Random Cantor Sets

With Professor Xiaolong Han at California State University, Northridge

Created a program that represents an N x N matrix where Discrete Fourier Transform was applied to each cell that corresponds to an alphabet set and removed particular cells which follows the Cantor set pattern.

Furthermore, we used the implications from the above and discrete Cantor sets to extend the FUP for random Cantor sets.

Published Research Paper

Las Vegas Klondike Solitaire

With Professor Michael Neubauer as an advisor at California State University, Northridge

Created a Monte Carlo simulation of Klondike Solitaire with efficient strategies that achieves a win-rate, on average, of 10%. Presented the topic at CSUNposium (the Annual Student Research and Creative Works Symposium).

Code

Main Menu