My work is motivated by the question of how we can ensure that technology – especially machine learning – is deployed in fair, trustworthy, and socially responsible ways. In particular, my research looks at how to certify robustness for machine learning algorithms in the presense of data poisoning or bias in the training dataset.
I graduated from Carleton College in 2018 with a BA in mathematics. Prior to starting grad school in the fall of 2020, I worked as a software developer at Epic in Madison. In my free time, I enjoy cooking (and eating!), Nordic skiing, reading fiction, running, and being outdoors.