Experienced researcher and engineer working at the Environmental Protection Agency as a contractor. Prior to the EPA, I completed my MSc in Chemical Engineering at Carnegie Mellon University where I was advised by Zachary Ulissi and worked on the development of an active learning framework for machine learning potentials to reduce computational time required for atomic simulations. Expert in data analysis and modeling through the usage of an extensive toolset including Python, Kubernetes and MongoDB. Excellent communication skills both verbal and written. Seeking to leverage my skills and experience in data science to address everyday problems using data-driven decision making.
Download my resuméM.S. in Chemical Engineering, 2020
Carnegie Mellon University
B.S. in Chemical Engineering, 2019
University of Tennessee, Knoxville
Developed an Active Learning Framework to Accelerate Atomic Simulations
Developed and tested different machine learning approaches to detect twitter bots
Developed a workflow to generate atomic structures and predict adsorbate energy
Worked on accelerating Atomic Simulations
Worked on Data Driven methods for Computational Toxicology
Using Deep Q-Learning to play games
A React App which visualizes popular sorting algorithms
A Django App [WIP]
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