Computational Optics for Near Field Imaging
Project Description
For many nano-scale structures in semiconductor fabrication process and biological analysis, existing optical techniques are either invasive or do not have the essential resolution due to various physical limits such as diffraction and photon limits. This project will investigate a type of near field imaging techniques by encoding the incident wave using new optical devices. The encoded signal will then be reconstructed by advanced learning-based algorithms involve phase recovery and generative models.
Start Date
August 1, 2026
Postdoc Qualifications
PhD in EE or CS
Strong publication record in computer vision venues such as, but not limited to, CVPR, ICCV, ECCV.
Understanding of photonic devices is preferred.
Co-advisors
Stanley Chan, stanchan@purdue.edu, ECE
Qi Guo, qiguo@purdue.edu, ECE
(We have been doing this recruitment for many years, and it has been approved for the past few years. We are just continuing this. We have complementary skills. Qi Guo focuses on optics / photonics, Chan focuses on algorithms and theory. We have several on-going projects.)
Bibliography
Junjie Luo, Yuxuan Liu, Emma Alexander, Qi Guo, Depth from Coupled Optical Differentiation, International Journal of Computer Vision, pp. 1-18
Nicholas Chimitt, Ali Almuallem, Qi Guo, Stanley H Chan, Wavefront Estimation From a Single Measurement: Uniqueness and Algorithms, arXiv preprint arXiv:2504.09395
MetaH2: A Snapshot Metasurface HDR Hyperspectral Camera, Yuxuan Liu, Qi Guo, To appear in 2025 IEEE International Conference on Image Processing (ICIP).
Nicholas Chimitt, Xingguang Zhang, Yiheng Chi, Stanley H. Chan, ‘‘Scattering and Gathering for Spatially Varying Blurs’’, IEEE Transactions on Signal Processing, vol. , pp. 1507-1517, Mar 2024.
Stanley H. Chan, ‘‘Computational Image Formation: Simulators in the Deep Learning Era’’, Journal of Imaging Science and Technology, vol. 67, pp.1-17, Nov 2023.