With a background in chemical engineering focused on environmental sustainability, I recognized the urgent need for decision-support tools that empower stakeholders at the front lines of climate action.

Driven by this need, I taught myself to code and collaborated with diverse teams—from politicians to marginalized well-diggers—to inclusively co-design digital products tailored to their unique challenges. These communities, deeply rooted in their local contexts, possess the holistic wisdom crucial to transform environmental data into actionable, real-world solutions.

To deepen my impact, I am currently pursuing a Master's in Computer Science at the University of Chicago, specializing in Machine Learning and High-Performance Computing (HPC).

My goal is to write energy-efficient, scalable code for performance-critical applications. I am particularly drawn to analyzing and unlocking potential for optimization across all layers of an AI product's stack, from the ML algorithm all the way down to the hardware.

I have 2 years of professional experience and graduate in March 2025. I am actively seeking full-time software and AI engineering roles in the US.

Let’s connect—I’d love to discuss potential opportunities!