About

Our department aims to be a diverse community engaged in areas of education and research in Statistical Theory and Methods, Data Science, Actuarial Science, Financial Mathematics, and Applied Probability; our research collaborations represent a wide range of interdisciplinary fields including environmental science, computer science, and biomedical science. We are home to the UCSB Center for Financial Mathematics and Actuarial Research, an interdisciplinary research center providing leadership in quantitative finance. We also provide consulting services through our Data Science Consulting Laboratory: DataLab

Diversity, Equity and Inclusion

At its core, our department views diversity and inclusion as critical within our mission to educate and prepare the future workforce of data scientists and quantitative thinkers. Increasing diversity across our field is essential in creating more productive, representative, and enriching outcomes as well as innovative solutions to critical problems. We recognize that historically, the job markets and academic communities in statistical theory and methods, financial mathematics, and actuarial science have been weighted toward racial, gender, and socioeconomically privileged communities. We are dedicated to correcting this imbalance in our own community.

PSTAT Department Calendar

April 2024

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04/24/2024 - 15:30 to 16:45
 
 
 
 
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Announcements

Professor Mike Ludkovski was awarded with California Climate Action Seed and...

Upcoming Seminars

Rita SahaRay 

Current: Visiting Professor,July 2022-June 2024: Department
of Statistics and Applied Probability, University of 
California, Santa Barbara,  USA
 
  1. April 24, 2024 - 3:30pm to 4:45pm
  1. Seminar
Professor David Dunson. Professor Dunson is the Arts and Sciences Distinguished Professor of Statistical Science, Mathematics and Electrical & Computer Engineering at Duke University. His research focuses on developing statistical methods for complex and high-dimensional data. Particular themes of his work include the use of Bayesian hierarchical models, methods for learning latent structure in complex data, and the development of computationally efficient algorithms for uncertainty quantification.
 
  1. May 1, 2024 - 3:30pm to 4:45pm
  1. Annual Sobel Lecture

Roberto Molinari is an Assistant Professor in the Department of Mathematics and Statistics at Auburn University. After an initial career in international political advisory, he obtained a PhD in Statistics at the University of Geneva (Switzerland) and successively had experience both as a statistical consultant for government and industry as well as a visiting professor at UCSB and Penn State University.

  1. May 3, 2024 - 3:30pm to 4:30pm
  1. Seminar