Full Name
Cynthia Rush
Job Title
Associate Professor of Statistics
Company
Columbia University
Speaker Bio
ChatGPT ChatGPT Cynthia Rush is an Associate Professor of Statistics in the Department of Statistics at Columbia University. She earned her Ph.D. in Statistics from Yale University in May 2016, working under the guidance of Andrew Barron. Prior to that, she completed her undergraduate studies at the University of North Carolina at Chapel Hill, where she obtained a B.S. in Mathematics.
Dr. Rush's research interests lie at the intersection of information theory, statistical physics, and applied probability. She focuses on addressing modern, high-dimensional inference and estimation problems, as well as complex machine learning tasks prevalent in the fields of statistics and data science. Her work aims to answer fundamental questions such as determining the amount of data or information required to solve a complex statistical problem, optimizing data utilization for gaining insights, and quantitatively characterizing the limitations of such insights. Additionally, she is involved in developing and analyzing the performance of computationally-efficient algorithms and procedures for statistical inference and estimation in these challenging settings.
Dr. Rush's research interests lie at the intersection of information theory, statistical physics, and applied probability. She focuses on addressing modern, high-dimensional inference and estimation problems, as well as complex machine learning tasks prevalent in the fields of statistics and data science. Her work aims to answer fundamental questions such as determining the amount of data or information required to solve a complex statistical problem, optimizing data utilization for gaining insights, and quantitatively characterizing the limitations of such insights. Additionally, she is involved in developing and analyzing the performance of computationally-efficient algorithms and procedures for statistical inference and estimation in these challenging settings.
Speaking At
Abstract
In this talk, I'll discuss my experiences and what I learned while I was working under the guidance of Andrew Barron as a PhD student at Yale University studying sparse regression codes and approximate message passing algorithms.
