Computational Imaging Lab @ Cornell

Prof. Kristina Monakhova

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!


Nov 2024 Kristina is giving an invited talk at MERL on Robust and Physics-informed machine learning for low-light imaging!
Nov 2024 Kristina is featured in an article on MIT News!
Jun 2023 Kristina will be joining Cornell’s Computer Sciences Department in Fall 2024 as an assistant professor!