Professor Gokul Upadhyayula
University of California, Berkeley
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 Prof. Valentine Vullev at 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 + LLSM project to image the entire fly brain and mouse cortical column with synaptic resolution. Gokul joined UC Berkeley’s faculty July 2019 to lead the Advanced Bioimaging Center (ABC) as its scientific director.
Gokul, 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, Gokul and his team will build two cutting-edge adaptive optical multi-functional microscopes to enable imaging across scales spanning several orders of magnitude in space and time, with, for example, specimens up to several millimeters in size, or over imaging sessions lasting up to multiple days. Consequently, the greatest challenge the users face is the ability to visualize, analyze and understand the explosively large quantities of immensely complex data. The primary goal of the ABC is therefore to provide both cutting-edge microscopy, and dedicated human and hardware resources capable of handling tera- to petabyte scale projects and developing robust, open source computational workflows that allow scientists to extract biologically meaningful insights.