Alex Pan
2022 PhD Fellow

Alex is an incoming PhD student in Computer Science at UC Berkeley, advised by Jacob Steinhardt. He is interested in making ML systems more robust and aligned with human values through better empirical and theoretical understanding of potential failure modes. Currently, he is working on using language to construct more resilient value functions and better control machine learning models. Previously, Alex completed a B.S. in mathematics and computer science from Caltech. For more information, visit his website.