The John Simon Guggenheim Memorial Foundation announces its 101st class of Guggenheim Fellows, featuring 223 remarkable artists, scientists, and scholars selected from nearly 5,000 applicants across 55 fields. Of these, one is an economist, and two are data scientists.

The John Simon Guggenheim Memorial Foundation has unveiled its 101st class of Guggenheim Fellows, recognizing 223 distinguished individuals from various fields. Chosen from a competitive pool of approximately 5,000 applicants, this year's Fellows represent an array of 55 disciplines, showcasing the best in artistry, science, and scholarship.

Edward Hirsch, President of the Guggenheim Foundation, expressed pride in the new class, highlighting their potential to contribute boldly to society's challenges. Each Fellow receives a monetary stipend to pursue independent creative work in an unfettered environment, continuing the Foundation's mission established in 1925.

This year's applicants saw a significant rise in submissions, with Creative Arts and Humanities applications increasing by 50% and Sciences by 86%. The selected Fellows range in age from 28 to 76 and include both established scholars and those without full-time academic affiliation.

Fellowships in fields related to economics, finance and data science were awarded to:

Ran Abramitzky (Economics)
Ran Abramitzky is Professor of Economics and Senior Associate Dean of Social Sciences at Stanford University. His research is in economic history and applied microeconomics, with focus on immigration and income inequality. He holds a PhD from Northwestern University. He is known beyond the field of economics for his 2022 book: Streets of Gold - America's Untold Story of Immigrant Success (affiliate link).

Yin Cao (Data Science)
Yin Cao is an epidemiologist at Washington University in St. Louis. Her focus is on how cancers develop, how to prevent them, and the impact on younger patients.

She is the principal investigator of her own lab, leading and collaborating on several ongoing research projects.

Dr. Cao earned her master's degree from Columbia University, and her doctor of science degree from Harvard University T.H. Chan School of Public Health.

Matias D. Cattaneo (Data Science)
Matias D. Cattaneo is a Professor of Operations Research and Financial Engineering at Princeton University and an Amazon Scholar. He studies the mathematical foundations of data science at the intersection of econometrics, statistics, machine learning, and artificial intelligence. His research develops statistical and computational methods for the social, behavioral, and biomedical sciences, with emphasis on program evaluation and causal inference.

He earned his Ph.D. in Economics and an M.A. in Statistics from the University of California, Berkeley, as well as a Master in Economics from Universidad Torcuato Di Tella in Argentina.

The Guggenheim Foundation has been dedicated to fostering creativity and scholarship since its inception, with nearly $450 million awarded to over 19,000 individuals, including 125 Nobel laureates. 

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