CSE Colloquium – Learning to Image: Computational Microscopy for Dynamic Systems
Presenter: Laura Waller, UC Berkeley
Abstract:
Computational imaging jointly designs hardware and algorithms to push beyond the classical limits of imaging, enabling measurement of new quantities (e.g. 3D, phase, and super-resolution) with simple, inexpensive hardware. These approaches have already transformed consumer photography; our goal is to achieve a similar transformation in scientific microscopy.
In this talk, I will show how end-to-end learning is reshaping the design of imaging systems, from programmable illumination with LED arrays to compact, lensless cameras built from Scotch tape. By combining physical models with neural networks, we can jointly learn how to capture data, reconstruct images, and self-calibrate systems that would otherwise be too complex to model. However, many computational methods rely on multiple measurements, limiting their use for live, dynamic samples. I will introduce new space-time algorithms based on implicit neural representations (INRs) that jointly recover structure and motion, correct artifacts, and enable high-resolution imaging in regimes where traditional approaches fail.
Bio:
Laura Waller is the Charles A. Desoer Professor of Electrical Engineering and Computer Sciences at UC Berkeley. She received B.S., M.Eng. and Ph.D. degrees from the Massachusetts Institute of Technology in 2004, 2005 and 2010. After that, she was a Postdoctoral Researcher and Lecturer of Physics at Princeton University from 2010-2012. She is a Packard Fellow for Science & Engineering, Moore Foundation Data-driven Investigator, OSA Fellow, and Chan-Zuckerberg Biohub Investigator. She has received the Carol D. Soc Distinguished Graduate Mentoring Award, OSA Adolph Lomb Medal, the SPIE Early Career Award and the Max Planck-Humboldt Medal.
Hosted by: Professor Alvaro Cardenas
Location: Engineering 2, Room E2-180 (Refreshments such as fruit, pastries, coffee, and tea will be provided.)
Zoom Option: https://ucsc.zoom.us/j/93445911992?pwd=YkJ2TQtF79h0PcNXbEcpZLbpK0coiY.1&jst=3