Stanford University
Showing 4,551-4,600 of 6,033 Results
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Alay Shah
Masters Student in Chemical Engineering, admitted Spring 2024
Bio→ Graduate Chemical Engineering student.
→ Previously, Process Engineer at Kite, a Gilead Company.
→ Bachelors in Biomedical Engineering at the University of Texas, Austin.
→ 5 years of experience working in cGMP pharmaceutical manufacturing and upstream process development. Working knowledge of cell and gene therapy, lean manufacturing, risk assessment &mitigation, IOPQ Validation, quality systems, eQRMS, asset lifecycle management, SAP ERP, Syncade MES, Oracle EBS, LIMS, ISO standards and FDA regulations.
→ Through Stanford's MS program, I aim to build upon my biomanufacturing experience, further developing my skillsets in bioreactor design and data analytics to model and improve standardized development of therapeutics for patients -
Serena Shah
Ph.D. Student in History, admitted Autumn 2021
Research Assistant, History DepartmentBioSerena is a PhD candidate in History in the United States field. She is in her fifth year and she works on the history of ideas in the nineteenth century, especially Americans' ideas about antiquity. Her dissertation investigates the history of oriental scholarship in the United States. It examines Americans' post-Civil War investment in pre-classical antiquity, and the 3,000-4,000 year-old history of the Bronze Age Orient (the site of the most ancient "Eastern" civilizations, or the modern Middle East). She is also currently writing a research article on Greek and Roman slave-naming practices and the classicism of American slavery.
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Yash Shah
Ph.D. Student in Computer Science, admitted Autumn 2025
Current Research and Scholarly InterestsMy research interests lie in developing neuroconnectionist mechanistic models of the brain that deepen our understanding of neural computation and representations. I aim to explore how physiological and anatomical constraints shape cortical topography and, in turn, scaffold development. I am particularly intrigued by observing certain behaviors emerge from mechanistic models, even when the model was not optimized to do so.
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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.
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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.
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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!
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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.
