Hometown: Marathon, Florida
Dual Degree: MS Energy and Earth Resources & Masters of Global Policy, Data Science Concentration, LBJ School of Public Affairs
Thesis Title: Decarbonization Technology and Policy Pathways for Texas
Thesis Supervisor: Dr. Michael Webber
A Little About Me
I am originally from the British Virgin Islands and went to high school in the Florida Keys where I grew up scuba diving, sailing, and kiteboarding next to a coral reef. I received my undergraduate degree in Physics with a concentration in Physical Oceanography because I wanted to help protect our earth’s oceans. I didn’t realize at the time, but that the most effective way to do that is to support the energy transition. I am now a master’s student at UT Austin studying EER (focusing in electricity markets and decarbonization) and Global Policy (concentration in data science) with a dream of working for a company that values building an equitable and fruitful future through accelerating decarbonization. I love problem-solving, collaborating on interdisciplinary teams, working hard to accomplish goals, and using data to understand macro trends that exist in our society. My past work experience has allowed me to critically think about energy from an efficiency and demand response perspective by working as an energy efficiency engineer, and from a financial investment perspective by working as a data analyst at a boutique hedge fund. In my free time, if I am not listening to “The Energy Gang” podcast, I am probably rock climbing, trail running, or riding my bike through the City of Austin.
I am currently working with Dr. Webber on “Decarbonization Pathways for Texas” and Dr Rai working on “Smart Decarbonization in the Nexus of Climate Change, Population Growth and Technology Adoption”. Both research efforts require a combination of data analysis, machine learning, and modeling skills to better understand existing energy trends within different sectors and how policy coupled with disruptive technology could impact those trends.
My career goal is to utilize data science as a tool to identify ways to accelerate the energy transition within theorized decarbonization technology and policy pathways.
Data Science, Energy Transition, Demand Response, Machine Learning, Modeling, Electricity Markets, Python, R