As a Machine Learning Climate Scientist at Stanford University, I develop tools to enable large scale urban decarbonization with satellite imagery. My research combines machine learning, remote sensing, geospatial analytics, and technical leadership to address one of the most pressing challenges of our time: climate change. I recently finished my PhD in Engineering at Stanford, where I have contributed to multiple publications and projects on computer vision, hyperspectral data, and urban knowledge graphs. In addition to my time at Stanford, I designed the machine learning infrastructure at AceCancer, a health tech startup that delivers bespoke recommendations to cancer patients. This implementation was made possible thanks to my background in software engineering from the IoT startup Yonomi, where I developed a skill set in containerization and deployment of production level code.