Stanford University
Showing 4,581-4,600 of 6,034 Results
-
Benjamin Shapero
Ph.D. Student in Earth System Science, admitted Autumn 2020
BioI am a geomicrobiologist and am broadly interested in the connections between protein biochemistry, environmental microbiology, and biogeochemistry. I hail from the surf town of Encinitas near San Diego. I completed my undergraduate studies at the University of Southern California (USC), where I majored in both Biological Sciences and Classical Saxophone Performance. At USC I volunteered in a cellular and molecular neuroscience lab, and it was there that I discovered my fascination with proteins. After graduation, I worked in a vaccine design lab at Scripps Research. This research fostered my growing fascination with protein biochemistry and further exposed me to the realm of microbiology. I have since followed my interests in proteins and microbiology, along with my longstanding passion for climate science, to the field of geomicrobiology. I am currently pursuing a Ph.D. in geomicrobiology at Stanford University in the Earth System Science department.
-
Sandro Sharashenidze
Ph.D. Student in Political Science, admitted Autumn 2024
BioSandro is a graduate student in political science who is interested in the intersection between international security, macroeconomics, and formal theory. Before joining Stanford, Sandro worked as a trading analyst and managed an education-focused NGO in Tbilisi, Georgia. He has a bachelor's in economics and a master's in international relations from the University of Chicago.
-
Mayank Sharma
Masters Student in Education, admitted Autumn 2024
Other Tech - Graduate, BiologyBioFirst year student at the Graduate School of Education (GSE), pursuing the Education Data Science (MS) program. Hit me up (masharma@stanford.edu) to discuss data science and/or education equity!
-
Rohan Sharma
Ph.D. Student in Geophysics, admitted Autumn 2025
BioI’m a Ph.D. student in the Department of Geophysics. My research explores the applications of quantum computing and scientific machine learning to geophysical problems, with a focus on modeling, inversion, and uncertainty quantification.
