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It’s been a really long time (nearly 9 months!) since I posted on this, but as a part of my ongoing professional development, I’ve decided that 2019 will see me posting weekly at the very least. I’ve been working on various projects behind the scenes, but I’d like to introduce two new projects that I will be working on in the coming future. One will be an independent project and another will be done with a close friend of mine. Without further ado, I’ll introduce the first project.
I remember when I first entered the mathematics department, I did it specifically because I saw just how excited the professors were about their field. Those first few months were obviously not super exciting as I hadn’t really done any math since high school, and at the time, I had no interest in it nor any interest in continuing it.
Before reading this, it’s important to have an understanding of The Secretary Problem, which is detailed in my previous post The Secretary Problem.
When perusing Cross Validated, I came across someone seeking to simulate the Secretary Problem which was summed up quite nicely by this problem text:
In my Generalized Linear Model class, we were tasked with proving that with high $\lambda$, the Poisson distribution approaches the standardized normal distribution. I went ahead and wrote up the proof for the extra credit and really enjoyed doing it. I’ll note that converting the exponential to a series was not my idea and had a little Stack Exchange inspiration. It reminded me how useful series expansions were, so that will hopefully prove useful in future research.
Bluetooth connected Windows GUI that allows you to text others without taking your phone out of your pocket.
Developed data organization structures for dedicated research dashboard for critical shipping concerns.
Point processes, specifically those on graphs, are of recent increasing interest in the applied mathematics community due to their wide range of applications. The inclusion of increasing types of point processes has allowed research to delve further into more complex and more realistic examples of graphs. In this case, I study Mat’ern II point processes, or hard shell points with some radius that annihilate each other to simulate real world objects interacting with each other.
Gaussian Processes have been utilized for a number of regression problems that we cannot assume any distribution on. The nonparametric qualities of gaussian processes allow for the development of a bayesian prior utilizing the observed points in the development of a posterior distribution. This method of model generation can be extended to a classification problem by applying the gaussian prior to a logistic regression problem. In this talk, I discuss examples of Gaussian Process Regression as well as an application on the MNIST dataset. The method is compared against other popular ML methods such as SVM, KNN, and MLP.
Undergraduate Enhanced Course, Austin Peay State Univeristy, Mathematics and Statistics, 2016
Statistics Instructing and Tutoring
During my undergraduate, I served as an instructor for the Academic Support Center for introductory statistics courses. This entailed teaching a supplementary course that assisted conditional students in their mathematics courses, algebra review, and referring to individual tutoring. During the Spring, this was a twice-a-week 1.5 hour classroom session, and during the summer, it occurred every day.
Undergraduate Course Lecturing, Austin Peay State University, Mathematics and Statistics, 2017
At the start of my graduate career, my mentor professor Dr. Jackie Vogel allowed me to co-lecture her College Algebra section and assist her with online Statistics Course. In the College Algebra course, I lectured every Friday and did any grading needed for the course. Towards the end of the semester, I began to teach Monday and Friday as well as wrote the penultimate and final exam. In the statistics course, I served as a discussion facilitator and handled quiz grading.