Rate My Professor Aurore Delaigle

Professor Aurore Delaigle is Professor of Statistics in the School of Mathematics and Statistics, Faculty of Science, at the University of Melbourne. Her career includes positions as Reader at the School of Mathematics, University of Bristol; Assistant Professor in the Department of Mathematics, University of California, San Diego; and BAEF Postdoctoral Fellow in the Department of Statistics, University of California, Davis. She held an Australian Research Council (ARC) Future Fellowship from 2013 to 2018. Delaigle's research specializations encompass nonparametric estimation methods, particularly for deconvolution and measurement error problems, functional data analysis, group testing problems, distributional learning, and statistical analysis of complex and streaming data. She has contributed to methodologies addressing bias in time-series data, COVID-19 group testing strategies, and spline techniques for incomplete data.

Delaigle has earned major awards and honors, including election as a Fellow of the Australian Academy of Science in 2020, Fellow of the American Statistical Association in 2018, the Committee of Presidents of Statistical Societies (COPSS) Presidents' Award (George W. Snedecor Award) in 2017, the Moran Medal from the Australian Academy of Science in 2013, and the Hellman Fellowship in 2006–2007. She is a Fellow of the Institute of Mathematical Statistics and an elected member of the International Statistical Institute. Notable publications include 'Achieving near perfect classification for functional data' with Peter Hall (Journal of the Royal Statistical Society Series B, 2012), 'Nonparametric density estimation from data with a mixture of Berkson and classical errors' (Canadian Journal of Statistics, 2007), co-editorship of Handbook of Measurement Error Models (Chapman & Hall/CRC, 2022), 'Mitigating Bias in Statistical Analyses of Data Collected Over Time' (2023), and 'Nonparametric estimation for streaming data' (2022). With an h-index of 35, her work has profoundly influenced nonparametric statistics and related fields. She has served on editorial boards and as Executive Secretary of the Institute of Mathematical Statistics.