Shalin received his PhD at the National University in Singapore in optics. After this graduate work, he was a staff scientist at the University of Chicago and a Human Frontier Science Program Fellow at the Marine Biological Laboratory in Woods Hole. Now Shalin is a platform leader in computational microscopy at the Chan Zuckerberg Biohub.
At the CZ Biohub, his team develops imaging and computational technologies to probe the physical properties of biological systems with more precision and efficiency. It is designed to work on multiple scales from organelles to tissues and integrates research from many fields including optics, machine learning and inverse algorithms.
More about his work: https://www.czbiohub.org/comp-micro/
- Quantitative label free cell imaging with phase and polarization can separate cellular structures through physical properties while providing a gentle environment for cells
- 2.5D UNet based deep learning models and quantitative label free imaging are computationally more efficient and almost as accurate as 3D UNets in virtual staining applications
- Cellular morphological states and transitions can be extracted from quantitative label free images using DynaMorph, a deep-learning framework