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Robert Webber earned a Ph.D. in Mathematics from New York University in 2021. He specializes in randomized numerical methods and their applications in data science and scientific computing. He teaches probability and data science courses at both the upper-undergraduate and graduate levels. Prior to his current position at the University of California, San Diego, he was a postdoctoral scholar at the California Institute of Technology from 2021 to 2024, where he worked under the supervision of Joel Tropp. His research interests lie at the intersection of mathematics and computational applications, focusing on improving algorithms for practical data analysis. Webber continues to contribute to the field through his dedication to teaching and research, intending to bridge theoretical methodologies with real-world data challenges.
California Institute of Technology • Pasadena, CA
Conducted research under the supervision of Joel Tropp, focusing on randomized numerical methods.
Administered by the Scripps Institution of Oceanography. Curricular groups include Climate-Ocean-Atmosphere (COAP), Geosciences (GEO), and Ocean Biosciences (OBP).