Computational Microscopy

We develop technologies for scalable analysis of biological systems.

Our research jointly optimizes the optical design and inverse algorithms to reveal physical properties of living systems with increasing precision, resolution, and throughput. We develop machine learning approaches to gain biological insights from this rich data. Our technologies are designed to be effective across scales of organelles, cells, organoids, and tissues. We pursue discovery of biological mechanisms and therapeutic opportunities in collaboration with Chan Zuckerberg Biohub’s initiatives, platforms, and university partners. Our interdisciplinary research spans fields of optics, inverse algorithms, machine learning, and biophysics.

Our current technological research is focused on:

  • Label-free imaging of density and order across biological scales.
  • Measurement of nanoscale order among molecules.
  • Inverse algorithms for vectorial imaging.
  • Machine learning algorithms to transform voxels into measurements.

We pursue collaborative biological research in:

  • Mapping myelination, cell types, and connectivity in brain tissue.
  • Detection of infectious pathogens and analysis of immune response.
  • Discovering architectural basis of cell and organelle function.