Resume

Work experience

Mentored and guided student teams to design, train, and launch analytics pipelines that cleaned, integrated, and visualized multi-modal datasets within a 13 week spring cycle
Revamped Colab-based coding modules to emphasize data extraction, data transformation, and data visualizations to boost student engagement.
Engineered interactive Plotly dashboards in Streamlit to translate student survey results into data driven insights that informed iterative improvements to the AI-4-ALL programs.

Developed a Bayesian hierarchical model in PyMC3 that achieved sub-3% error for robust parameter estimation for complex highly variable time-series datasets.
Employed Gaussian Process models using Celerite to denoise multi-modal time-series datasets to enhance signal clarity for forecasting analysis.
Optimized Python code to create a lightweight Matplotlib application that visualized metric evolution over time to simplify complex concepts for non-technical stakeholders.

Published several peer-reviewed manuscripts on using unsupervised machine-learning frameworks to create clean, analysis-ready data catalogs.
Constructed SQL - Python pipelines to extract, transform, and load multi-sourced astronomical datasets to create a unified, queryable database.
Increased pattern detection sensitivity by 11% through probabilistic clustering algorithms with Scikit-Learn within large, noisy datasets.

Ph.D in Astrophysics, Vanderbilt University, 2023
- Thesis: Characterizing Open Clusters and Spectroscopic Eclipsing Binaries with Machine Learning Frameworks
M.S. in Physics, Fisk University, 2017
B.S. in Astronomy, University of Florida, 2011