Patrick is motivated (maybe too motivated), educated (probably too educated), and enthusiastic (definitely too enthusiastic!). He is currently seeking an internship for the Summer of 2020.
Read Patrick's resume if you haven't already!
Read some of Patrick's written work.
In this project I explore the effectiveness of various sampling algorithms in solving the informative path planning problem. In this case the task is to learn a 2D field (e.g. temperature map). The belief state of the field is modelled using a Gaussian Markov Random Field (GMRF) which is sequentially updated with Bayesian conditioning. The paths are planned to minimize the variance of the belief state.
In this project I implement the expectation maximization (EM) algorithm for a mixture of Gaussians model. Here the EM algorithm iteratively updates the covariance matrix, and mean and weight of each cluster.
In this project I create connect-4 AI players using a minimax tree search algorithm with alpha-beta pruning and other added heuristics (e.g. favoring the middle, and favoring having rows of 2, 3).