I am a data scientist at Flatiron Health, where I use machine learning on real-world datasets to accelerate cancer research.
My background is in computational cognitive neuroscience. I have been a Simons Fellow at NYU, a PhD student at Stanford, a lab tech at MIT, and an undergrad at Amherst. My academic research focused on the neural basis of higher-level cognitive processes such as learning and decision-making.
I am also interested in building tools that can help people understand quantitative data. I am the creator of seaborn, a Python library for data visualization, and I have originated or contributed to several other open source projects.