Isaac Gibbs
Graduate Student, UC Berkeley
Isaac Gibbs is a fifth year PhD student in the Stanford Statistics Department advised by Emmanuel Candès. Previously, he completed a BSc in Math and Computer Science at McGill. His research develops new methods for quantifying the uncertainty underlying predictions made by black-box models (e.g. neural nets, random forests).