Growing up in Guatemala and Germany, I have always been fascinated by the interplay of language and technology. My multicultural background led me to study a mixture of political science and economics, as an undergraduate student at Stanford University. Towards the end of my undergraduate degree, I became fascinated by the ability of machine learning to model complex cognitive phenomena. As a computer science master’s student at Stanford, I worked together with Dan Jurafsky to build deep learning models to automatically detect and remove bias in news articles. During my PhD in Computer Science, I hope to use insights from how the human brain understands language to improve machine learning and natural language processing models. By leveraging similar mechanisms used in the brain to process language, I believe it is possible to build models that require less data and computation and which can accordingly be more effectively applied to low-resource languages and domains.