Brian is a recovering biologist, a graph theory groupie, and a student of anything that grows, learns, or evolves. He graduated cum laude with a B.S. in Bioinformatics from BYU in 2019, completed a master’s in Environmental Science at BYU in August, 2021, and is currently pursuing a PhD in Computer Science as a member of IDeA labs. He is excited to be researching relationships between network structure and parameter identifiability in systems as a means of understanding why large systems such as neural networks, protein interaction networks, and ecological networks organize themselves as they do. His previous research has involved leveraging signal processing and machine learning to characterize environmental controls of streamflow regime and stream water quality, as well as applying network theory to understand the effect of training on artificial neural network structures. Brian is also an avid swimmer, a composer of orchestral music, a mediocre cook, and a skilled botanist.