I graduated from Harvard in 2017 where I studied computer science and math. At Harvard, I did research in deep learning, natural language processing (in particular, text summarization), and generative modeling with the Harvard NLP group. After graduating, I worked on computer vision and robotics at a startup, rounding out my experience in all things machine learning. Recently, I joined the Google AI residency as a chance to work with top researchers in AI, machine learning, and language understanding. I feel very lucky to be able to collaborate with brilliant mentors and colleagues from all of these fields, and I have a ton of freedom to pursue the research directions I find most interesting. Google AI, with its abundance of talks, strong computing infrastructure, and world experts sitting nearby, has been a fantastic research environment for me to grow in. Currently, I am interested in understanding how to build language primitives that are transferable across tasks -- especially representations that can encode concrete world knowledge. Such representations are essential for robust and interpretable AI, especially when using opaque and complicated deep learning systems learned from data. Outside of research, you can find me playing basketball, cooking, or taking day trips to remote beaches.