Data Science. Artificial Intelligence.
My professional and academic experiences converge on understanding complex systems, measuring what matters and using data to drive better decisions.
A foundation in Chemistry developed my appreciation for quantitative analysis, experimentation and evidence-based reasoning. Over time, that evolved into a broader focus on performance evaluation, root cause analysis, continuous improvement and data-driven problem solving. The transition to Data Science and Artificial Intelligence was a natural progression, extending these same principles to increasingly complex systems and larger-scale decision making.
To me, the appeal of AI is not just the technology itself, but the challenge of developing systems that perform reliably in real-world environments. Success requires more than model development; it requires thoughtful evaluation, an understanding of tradeoffs, clear definitions of success and a disciplined approach to measuring outcomes.
My graduate work in Data Science has provided the technical foundation to develop Machine Learning and AI-driven solutions. My broader background has shaped how I think about them, not simply as models to be optimized, but as systems that must be evaluated, improved and ultimately judged by the value they create. This multidisciplinary perspective allows me to bridge analytical rigor, operational thinking and modern AI capabilities when approaching complex challenges.
A real-time gaze-to-speech tool that gives people with physical disabilities a voice using only their eye movements.
Using XGBoost to predict wildfire occurrence across 3, 7 and 14-day horizons.
Helping engineering and marketing teams get fast, audience-tailored answers from GenAI research documents.
A bidding agent for a simulated second-price ad auction that infers each user's value from observed behavior.
A research proposal examining racial disparities in clinician empathy during childbirth.
A multiple regression analysis investigating whether age predicts sleep duration, using CDC survey data.
A program that finds every valid word in a Scrabble rack, including wildcards, then scores and ranks them.
A convolutional neural network that reads retinal images and flags which patients should be referred for treatment.
A Neo4j graph of global refugee flows that uses network centrality to surface the top sending and receiving countries.
Interactive D3.js visualization investigating how caffeine intake relates to stress across 20 countries.