Computational imaging involves the joint design of optical systems and post-processing algorithms such that computation replaces optical elements, enabling simple experimental setups. This talk will describe new optical microscopes that employ simple experimental architectures and efficient nonlinear inverse algorithms to achieve high-resolution 3D and phase images. By leveraging recent advances in computational illumination, we achieve brightfield, darkfield, and phase contrast images simultaneously, with extension to 3D and gigapixel phase imaging. We discuss unique challenges for large-scale real-time imaging of biological samples in vitro and in vivo.
The BIDS Data Science Lecture Series is co-hosted by BIDS and the Data, Science, and Inference Seminar.
Laura Waller is an assistant professor at UC Berkeley in the Department of Electrical Engineering and Computer Sciences (EECS), with affiliations in Bioengineering and Applied Sciences & Technology. She was a postdoctoral research associate in electrical engineering and lecturer of physics at Princeton University from 2010-2012 and received BS, MEng., and PhD degrees in EECS from the Massachusetts Institute of Technology in 2004, 2005, and 2010, respectively. She is a Moore Foundation Data-Driven Investigator, Bakar fellow, NSF CAREER awardee, and Packard Fellow.