As a doctoral student in the Earth System Sciences Department at Stanford University, I am a researcher under the guidance of Professor Jen Burney with a commitment to addressing critical challenges in climate science and food security. I hold triple bachelor’s degrees in Physics, Astrophysics, and Applied Mathematics from the University of California, Berkeley, where I cultivated a comprehensive analytical background and honed expertise in quantitative research, machine learning, and large scale physical systems. My background working as an aerospace engineer and developing AI systems for automotive engineering provides me with a uniquely critical perspective to experimental systems.

Research and Career Intentions

As a first-year graduate student at Stanford working with Professor Jennifer Burney, my intention is to develop advanced machine learning algorithms and geospatial metrics to improve simulations of food insecurity in response to climate-driven disasters. During my PhD program, I plan to integrate remote sensing and deep learning methods to deliver actionable, high-resolution predictions for emergency responses in vulnerable regions, focusing on scalable solutions for the global south. Outside of research, I have taken on the role of being a Graduate Student Action Committee (GSAC) representative in the Earth System Sciences (ESS) department. I hope to be a supportive voice for the students in my community to the administration, as well as take on mentoring roles to younger students in new PhD cohorts.

Long term, my goal is to be a leader in the intersection of data science and humanitarian aid, building systems that optimize disaster response and food distribution worldwide. I aspire to use my expertise from both academia and industry to innovate modeling technologies and to create initiatives dedicated to advancing science-driven, equitable solutions for climate resilience and food security. Additionally, I hope to continue mentorship in later stages of my career, focusing on pushing students, and those from underrepresented backgrounds, to take on climate and food security related issues in their own communities. By mentoring future scientists and developing sophisticated algorithms for geospatial analysis, I hope to foster broader societal impact and drive progress at the interface of technology and humanitarian causes.

Professional Experience

Professionally, I have served as a Solutions Architect at Amazon Web Services, leading the design and deployment of advanced machine learning initiatives such as the AWS IGNITE platform, and automated CAD tooling for automotive and aerospace manufacturing engineering customers. My experience also extends to cross-functional projects involving urban heat analysis, international sustainability efforts, and contributions to space technologies. I bring to each endeavor a record of managing research and technical projects in complex multidisciplinary settings.

Technical Competencies and Leadership

My technical proficiencies include Python programming, advanced machine learning, satellite remote sensing, and hardware prototyping. My skills are listed below:

• Java
• Python
• SQL
• Unix
• Latex
• Amazon Bedrock
• Amazon S3
• AWS Sagemaker
• AWS Fargate
• GIT
• Matlab
• Simion
• ssh
• Arduino
• LabVIEW
• Solidworks CAD
• Openrocket
• Fusion 360
• Ansys Simulations
• Soldering
• Waterjetting
• Lasercutting
• Lathing
• Nanodevice microfabrication
• HAM Radio Certified Technician

I am deeply invested in educational outreach, having founded the STARxNexGeneGirls Scholarship Program at Berkeley and led the STAR rocketry team at the executive level. My research trajectory is guided by the pursuit of scientific advancement for tangible societal benefit. I hope to continue mentoring and advancing the next generation of engineers and scientists. Please reach out!