aidanlokeeffe / nicu_hrv_analysis

The purpose of the project was to investigate how heart rate variability metrics may be used to predict sepsis in preterm infants, and to present this work with an understandable report.

Hello! My name is Aidan O'Keeffe. I'm currently a Data Analyst I with the Railroad Commission of Texas's Critical Infrastructure Division. I hold a Bachelor of Science in Mathematics from the University of Texas at Austin, and my educational background consists of mathematics, computer science, and statistics. I'm aspiring to be admitted to UT's Online Data Science Masters so I can learn about the theory and practice of this field.

Purpose

I do hope that if I become a data scientist, I can use my skills to make big positive changes to the world. The financial gains I stand to make are also a big motivator; I could get on top of my student loans and save enough money to feel comfortable starting a family. However, the thing that actually kicks me out of bed and makes me want to learn this stuff is that I find it so interesting. I love seeing big math step in to solve big problems.

Ongoing activities

I always have lots of ideas, which is why I have a bunch of repositories. Alas, you can only focus on so many things at once. My current activities, in order of priority, are:

1. Focusing on performing well at work,
2. Progressing through Google's Advanced Data Analytics Career Certificate, and
3. Trying out new ideas as they come for a network science research problem I've been working on for a few years.

Completed projects

Excluding the things I do at work (which I can't share without clearing it with my manager first), these are the projects I've completed that I'm most proud of:

1. Analysis of Heart Rate Variability in Preterm Infants to Predict Sepsis, completed 1/19/2023.
2. Bevonia: Princess Knight, completed 12/9/2018. This is slow to load, but it will.

Background

For a more in-depth look at my professional activities, you can visit my LinkedIn.

I graduated from UT Austin in the spring of 2021 with:

1. A Bachelor of Science in Mathematics, and
2. The Elements of Computing Certificate, a suite of courses in Python programming and computer science.

Of all my coursework, extracurriculars, and soft skills, those most relevant to data science are:

1. Probability, statistics, and stochastic processes,
2. Python and R,
3. Dynamical systems, optimization, and numerical analysis, and
4. Independent learning, research, and presentation skills.

Since graduating, I've had ecclectic experiences in school, work, and life which have finally paid of in the form of a salaried data analyst position:

1. Summer 2021: Completing an NSF funded research internship in network science,
2. Fall 2021: Joining up with an AI consulting startup,
3. Spring 2022: Bereavement and gearing up to return to school,
4. Summer 2022: Undergraduate biology and physics coursework,
5. Fall 2022: Completing an undergraduate reserach course,
6. Spring 2023: Breaking my ankle and completing Google's Data Analytics Certificate, and
7. Summer 2023: Getting hired as a data analyst with the Railroad Commission of Texas and starting the Google's Advanced Data Analytics Certificate.