Event Date
Leyla Kabuli is a fifth year PhD Candidate in Electrical Engineering and Computer Sciences
(EECS) at UC Berkeley advised by Professor Laura Waller - "Designing lensless imaging systems to maximize information capture"
Ben Mattison, PhD (Yang Lab) - "High-throughput two-photon miniaturized microscope"
Abstract for Designing lensless imaging systems to maximize information capture:
Mask-based lensless imaging systems use an optical encoder (e.g., a phase or amplitude
mask) to capture measurements, then a computational decoding algorithm to reconstruct
images. In these systems, measurements are no longer designed for direct human
interpretation, but instead for computational processing. As a result, the information content
available in measurements matters more than their visual interpretability.
In this talk, I will introduce a data-driven framework for lensless imaging system design
based on quantifying measurement information. I will provide an overview of our mutual
information estimation approach, which evaluates and optimizes imaging systems using
only raw measurements and noise characterization, without requiring reconstruction
algorithms, system modeling, or ground truth data. Using this framework, I will formalize the
object-dependent nature of lensless imaging, demonstrating that system designs should be
tailored to object sparsity, and present information-optimal encoder designs for compressive
imaging. Finally, I will discuss how these design principles connect to real experimental
systems, including our ConvRML lensless imager, and how information-driven design
generalizes across computational imaging applications.
Biography:
Leyla Kabuli is a fifth year PhD Candidate in Electrical Engineering and Computer Sciences
(EECS) at UC Berkeley advised by Professor Laura Waller. She received a BS in EECS and a
BA in Music from UC Berkeley in 2021, graduating as the 150th University Medalist. Her
research is in computational imaging, at the intersection of information theory, machine
learning, and optics. She is supported by the National Science Foundation Graduate
Research Fellowship Program and the Berkeley Fellowship