Stanford University
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Makyla Ann Cervantes
Undergraduate, Vice Provost for Undergraduate Education
BioMakyla is a student apart of Stanford's Class of 2028 whose ambition for business management and entrepreneurship has paved way for her community-uplifting endeavors! From founding her 501(c)3 nonprofit at 14 years old, scaling the company to provide 1,250+ low-income Latino students accessible dance opportunity, managing over $75k in assets, to being profiled on "Celebrations With Lacey Chabert" and attaining a $10,000 grant from Hallmark Media, to establishing the Women In Business Association where graduate Cal Lutheran and Pepperdine students mentored 300+ aspiring businesswomen, she ensures her pursuit of business further enriches female and Latino societies.
Makyla Cervantes will major in management science & engineering where she plans on intertwining economic, political, and technological industries to further Silicon Valley's innovative advancements! She cannot wait to explore the many dance, entrepreneurship, and Christian organizations on campus, uplifting the student body in any way possible. Here is to the next four, go trees! -
Giovanna Ceserani
Professor of Classics
Current Research and Scholarly InterestsIntellectual history, data science in the humanities, ancient and modern historiography, history of archaeology, early modern travels and explorations of the past
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TAMER ÇETIN
Affiliate, Medicine - Primary Care and Population Health
BioTamer Çetin is a Research Professor at Stanford whose work focuses on applied econometrics, causal inference, and machine learning. His research develops robust methods for statistically reliable empirical analysis in high-dimensional and complex-data settings, with contributions spanning weak identification, instrumental variables, regression discontinuity, debiased machine learning, and causal estimation.
At Stanford, he connects modern statistical learning methods with classical questions in identification, inference, and policy evaluation. His research seeks to improve the credibility of empirical conclusions when researchers face complex data, competing identification strategies, imperfect instruments, or model uncertainty.
Before joining Stanford, Dr. Çetin held research and teaching positions across academia, consulting, and industry. He has taught courses in economics, econometrics, and data science. His broader research interests include causal inference, health economics, and the use of machine learning in empirical research.
