Kevin Liang
Adelphi University, NY·Physics
Telescopes, microscopes and cameras all hit a resolution limit: below a certain size, fine details blur together and cannot be told apart. A newer approach called modal imaging, which sorts incoming light into distinct patterns rather than simply recording brightness on a detector, can partly get around this limit.
- Fields
Physics
Engineering
Mathematics & Statistics
- Topics
superresolution
modal imaging
quantum-inspired imaging
- Grants
- 1 known grant, through Jul 2027
What they work on
- Derive Fisher Information matrices, a statistical measure of how precisely image features can be estimated, for imaging systems with off-axis aberrations to test whether they outperform aberration-free systems.
- Verify resolution gains of aberrated systems using maximum likelihood estimation on both simulated data and experimental optical data.
- Design aberrated imaging systems that outperform conventional ones when estimating multiple object parameters at once under the constraints of realistic systems.
- Develop theoretical multi-stage imaging designs in which prior measurements supplement modal imaging, extending its ability to get past conventional resolution limits.
More about the research
But practical drawbacks have kept it from replacing conventional imaging. This project examines those drawbacks and also explores a surprising idea: that lens flaws called aberrations, usually seen only as harmful, might help a system resolve a scene better.
Why it matters
Sharper imaging helps any field that must pick out detail in complicated scenes, including astronomy and biological imaging. Showing that aberrated or modal imaging systems can beat conventional resolution limits could lead to improved telescope, microscope and camera designs.
Known grants
From NIH and NSF research grants. Labs often have other funding we can't see.
Closest labs
Mikael Backlund
University of Illinois Urbana-Champaign, IL·Chemistry·Early-career
Establish the fundamental limits on spatial resolution for single molecules that do not photoswitch, using quantum parameter estimation theory, which sets the best precision achievable from the emitted photons.
Yulei Jiang
University of Chicago, IL·Mathematics & Statistics
Derive weighted ROC estimation algorithms that assign a weight to each case, covering the non-parametric, conventional binormal and proper binormal models, using maximum-likelihood derivation and validation against Monte Carlo simulations.
Peter T. So
Massachusetts Institute of Technology, MA·Biomedical Engineering
Design optical compression schemes for differentiable microscopy by training front-end optics and the decompression algorithm together as one neural-network auto-encoder.
The school
Adelphi University: 2 labs on PI Pages.
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