Jonathan Huggins (MA214 project lead) is an Assistant Professor of Mathematics & Statistics and Computing & Data Sciences. His research interests are broadly in large-scale, statistically robust uncertainty quantification, with applications to ecological modeling and scientific discovery using high-throughput and multi-modal genomic data. He regularly teaches MA214 Applied Statistics and MA586 Stochastic Methods for Algorithms. He is excited about introducing students to the computational tools that are so critical to many modern statistical methods.