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Newark, NJ · Sep 2023 – Present
I support two Navy-funded programs—Predictive Analytics for Ship Scheduling (PASS) and Rubric-Based Intelligent Curation of Navy Documents (RUBICON). Across these projects, I lead a three-person research team responsible for delivering both the underlying machine learning research and the production software that powers our predictive-maintenance models and RAG-based knowledge tools. My work spans model design, Python services, Postgres-backed data assets, and user-facing interfaces, and I regularly present our progress and operational impact to Navy leadership and project stakeholders.
Remote · Nov 2024 – Apr 2025
Materium tapped me to build an inverse-design loop for polymer nanocomposites. We shipped a Flask application that suggests viable recipes from optical requirements, then hardened the infrastructure so their team could scale experimentation with confidence. Mentoring Materium’s engineers on deployment patterns was as central as writing the models.
Chicago, IL · Feb 2023 – Aug 2023
At TTI-Chicago, I explored how PPO variants shape reinforcement-learning-from-feedback outcomes for large language models. Running hundreds of GPU experiments and instrumenting them with Weights & Biases revealed teacher-model choices that drove 5–15% gains on alignment metrics and informed the lab’s roadmap.
Chicago, IL · Jun 2022 – Oct 2022
I partnered with chemists to modernize forecasting across time-series signals. Pairing stacked ensemble models with Bayesian feature selection gave the team a 60% lift in property estimation accuracy and a more reliable view of manufacturing variability.
Hahnville, LA · Jul 2019 – Jul 2021
Supporting one of Dow’s largest Gulf Coast facilities taught me to orchestrate complex control systems and collaborate across operations, safety, and research. That exposure to data-rich industrial environments sparked my move into machine learning.
I completed my M.S. in Statistics at the University of Chicago, where I focused on self-supervised learning research and sharpened my experimental design skills. Before that, I earned a B.S. in Chemical Engineering with a Mathematics minor from Villanova University, grounding me in rigorous systems thinking.
That mix of statistical theory and engineering practice helps me translate abstract models into tools that perform in production.