Benjamin Chidester is a post-doctoral researcher in the Computational Biology Department within the School of Computer Science at Carnegie Mellon University. His research focuses on studying spatial patterns of the transcriptome and proteome using machine learning, computer vision, and signal processing. In particular, he studies the development of novel algorithms to analyze and model variation in cell phenotypes to better understand the processes that regulate the cell and those that contribute to disease, specifically cancer. He earned his Ph.D in the Department of Electrical and Computer Engineering at the University of Illinois at Urbana-Champaign. His research has been supported by fellowships from MIT Lincoln Labs and the CompGen Initiative at UIUC.