Conference on Advances in Bayesian and Frequentist Theory and Methods for Complex Data

Rutgers University New Brunswick, New Brunswick NJ

Investigators

Abstract

This project supports the Conference on Advances in Bayesian and Frequentist Theory and Methods for Complex Data, which will be held on April 8-9, 2022 at Rutgers University, Piscataway, New Jersey. The conference will bring together established, mid-career, and early-career researchers with diverse expertise to discuss the latest advances, current challenges, and emerging directions in statistical theory and methodology, with a particular focus on high dimensional problems. The conference will provide an important venue to stimulate interdisciplinary collaboration for tackling problems involving large and complex data. This initiative will also provide support for participation of early-career researchers and graduate students, including women and those from underrepresented minority groups. There has been a substantial and diverse development in statistical sciences to analyze and extract knowledge from high-dimensional and complex data, which can be found in various settings, from scientific research to industrial applications. Such development has often been powered by the connection and cross-fertilization between frequentist and Bayesian statistics. This conference will provide a unique opportunity for direct comparison and connection between frequentist and Bayesian approaches in high dimensional settings. The event will feature 18 plenary talks which will highlight the most recent research results in the field. A poster session will also be organized to encourage presentations from early career researchers and graduate students. More information can be found on the conference webpage: https://www.stat.rutgers.edu/conference-on-bayesian-and-frequentist-theory-and-methods This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.