Reverie Labs is rethinking early-stage drug discovery using machine learning. At Reverie, I'm helping to develop best-in-class models for virtual screening and lead optimization of pre-clinical cancer therapeutics.
I concentrated in Computer Science with a focus in Mind, Brain, and Behavior, a highly interdisciplinary program of study that draws on ideas and methods from computer science, cognitive science, neuroscience, psychology, linguistics, and philosophy.
I interned at Google AI / Google Brain during summer 2017 and 2018. In 2017, I worked on the AI Perception team, applying deep learning to the problem of multilingual character recognition. In 2018, I worked on the Tensorflow team within Google Brain, democratizing machine learning and deploying Tensorflow models across a wide range of Google products as part of the company's AI-first strategy.
I worked as a research assistant at the Fedorenko Lab at MIT from summer 2016 through 2018. The Fedorenko Lab uses neuroimaging and behavioral methods to construct computational models for language processing in the brain. As part of my research, I developed an unsupervised ML algorithm to extract semantic information from GloVe vectors as part of the IARPA Knowledge Representation in Neural Systems (KRNS) project.
HSMBB is an undergraduate organization that regularly hosts events, talks, and symposia on a wide range of topics related to cognitive science. I served on the board of HSMBB throughout my time at Harvard, including a year as chair.