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Advanced Bioimaging with Cutting-Edge Microscopy

Award Imaging Scientist

Funding Cycle Cycle 1


Srigokul Upadhyayula, PhD

University of California, Berkeley (Advanced Bioimaging Center)


Srigokul (Gokul) Upadhyayula’s research interests bridge applied engineering with basic science. He studied the charge transfer properties of cyanine dyes and bioinspired electrets using ultra-fast femtosecond spectroscopy as a doctoral student with Valentine Vullev at the University of California, Riverside. Gokul joined Tom Kirchhausen’s group at Harvard Medical School/Boston Children’s Hospital as a postdoctoral fellow, where he focused on questions addressed at a molecular level using lattice light-sheet microscopy (LLSM) with high temporal and spatial resolution. In parallel, Gokul joined Eric Betzig’s group at Janelia Research Campus as a visiting scientist, where he collaborated on the adaptive optical LLSM project to investigate sub-cellular dynamics within the natural environment of multicellular organisms such as zebrafish embryos, and on the expansion microscopy and LLSM project to image the entire fly brain and mouse cortical column with synaptic resolution. Gokul is now the scientific director for the Advanced Bioimaging Center (ABC) at UC Berkeley.

Project Description

Dr. Upadhyayula, along with ABC co-founders Nobel Laureate Eric Betzig, Xavier Darzacq, Doug Koshland, and Robert Tjian, aims to bring scientists with broad specialties (instrumentation, biology, applied mathematics, and computer science) together and provide free access to advanced imaging systems and resources. To start, he is building two cutting-edge adaptive optical multi-functional microscopes to enable imaging across scales spanning several orders of magnitude in space (specimens up to several millimeters in size) and time (imaging sessions lasting multiple days). The ABC seeks to provide cutting-edge microscopy and dedicated human and hardware resources capable of handling tera- to petabyte scale projects, and to develop robust, open source computational workflows that allow scientists to extract biologically meaningful insights.