SLAC National Accelerator Laboratory
Showing 1,141-1,160 of 1,925 Results
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Michael P. Minitti
Senior Scientist, SLAC National Accelerator Laboratory
BioA native of Arizona, I studied chemistry at Mesa Community College and Arizona State University, receiving my bachelor’s degree in 2000. I then did graduate work in chemistry at SUNY Stony Brook and Brown University, eventually specializing in time-resolved studies of the dynamics of chemical reactions. Following my interest in combining chemistry with ultrafast lasers, I did postdoctoral research at Princeton and Brown before joining SLAC as a staff scientist in 2011.
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Patrick Gerald Mitchell
Staff Engineer, SLAC National Accelerator Laboratory
Current Role at StanfordDirector of Operations at the Stanford-SLAC CryoEM Center
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Samsuzzoha Mondal
Research Assoc-Experimental, SLAC National Accelerator Laboratory
BioSamsuzzoha Modal is a Research Associate at SLAC National Accelerator Laboratory and a Ph.D. chemist specializing in advanced microscopy and biophysical chemistry. His research integrates protein engineering, structural biology, and quantitative imaging to understand how protein organization across length scales regulates biological activity, and to translate these mechanistic insights into therapeutic and diagnostic approaches.
Samsuzzoha earned his Ph.D. at the Tata Institute of Fundamental Research (Mumbai, India), where he developed chemical tools to image signaling phospholipid dynamics in live biological systems. He then completed postdoctoral training at the University of Pennsylvania (Philadelphia), building in vitro reconstitution models to study the molecular basis of membrane trafficking. Since 2023 at SLAC, he has been combining X‑ray crystallography, small‑angle X‑ray scattering, and advanced optical methods to uncover design principles for quantum biosensing tools and to support structure‑guided small‑molecule therapeutic development.
A committed educator and mentor, Samsuzzoha has taught bioanalytical chemistry and led diverse student teams, emphasizing inclusive, hands‑on training, reproducible data practices, and translational problem‑solving.
