Computational Imaging Lab @ Cornell
We combine ideas from machine learning, signal processing, optics, computer vision and physics to build better imaging systems (cameras, microscopes, and telescopes) through the co-design of optics, algorithms, and high-level tasks. Our aim is to design the next generation of smart, computational imagers that fuel scientific discovery, robotics, and medical diagnostics. We are particularly interested in:
- Differentiable optics - Can we use data and machine learning tools to design better cameras, microscopes, and telescopes?
- Physics-informed machine learning - How can we effectively combine our knowledge of imaging system physics with deep learning?
- Task-based imaging systems - What's the best camera or microscope for high-level tasks, such as robotics or medical diagnostics?
- Inverse problems and neural representations: Can we leverage neural priors to improve our imaging systems for microscopy and photography?
Check out our previous research projects and publications for more information!
news
Apr 2024 | Kristina is a poster and demo chair for ICCP in Lausanne, Switzerland this year! Submit your work to our Call for Posters, Demos, and Outreach by May 10! |
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Apr 2024 | Kristina is co-organizing the CVPR Computational Cameras and Displays Workshop in Seattle this June! Come check out our amazing speaker line-up, and our posters & spotlights! |
Mar 2024 | Cassandra won a Best Paper Award at SPIE Photonics West for her work on Leveraging Uncertainty Quantification for Adaptive Multiphoton Microscopy! |