We develop computational microscopy 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.
Shalin Mehta, Ph.D.
Postdoc: Human Frontier Science Program Fellow, Marine Biological Laboratory, Woods Hole
PhD: Optics, National University of Singapore
Syuan-Ming Guo, Ph.D.
Imaging Data Scientist
PhD & Postdoc: MIT, focusing on physical chemistry and data analysis.
Ivan Ivanov, Ph.D.
PhD: Stanford University, focusing on single-molecule biophysics.
Bryant Chhun, M.S.
Imaging Scientist: Singular Bio
MS: UCSF, focusing on super-resolution microscopy.
Janie Byrum, Ph.D.
PhD: University of New Mexico, focusing on immunology and microcopy
Cameron Foltz, B.A.
BA: Duke University, focusing on
physics with minor in philosophy.
Arunabh Ghosh, B.Tech.
MS: University of California, Los Angeles, in electrical and computer engineering
Interested in working with us?
To inquire about opportunities, send an email with a CV, and concise statements of your scientific interests and career interests. We value strong foundation, good work ethic, and interest in solving important problems with collaborative colleagues over past experience in our areas of focus.
If you are based at one of the three partner universities (UC Berkeley, UCSF, and Stanford), we have mechanisms for internships and long-term collaborations.