Nancy Reid

Nancy Reid is affiliated with the University of Toronto in Canada and has a research focus primarily in the field of Mathematics. Their work extensively covers areas within statistics and probability, artificial intelligence, and astronomy and astrophysics. The subfields involving statistics and probability dominate their research contributions, including aspects such as statistical methods, Bayesian inference, and uncertainty quantification.

The scientist's prolific output includes notable papers published in various academic venues. Recent papers include:

• The ASA president's task force statement on statistical significance and replicability, 2021, The Annals of Applied Statistics
• The Foundation is Available for Thinking about Data Visualization Inferentially, 2021, Harvard Data Science Review
• ASA President's Task Force Statement on Statistical Significance and Replicability, 2021, CHANCE
• Modified Likelihood root in High Dimensions, 2020, Journal of the Royal Statistical Society Series B (Statistical Methodology)
• Variability of extragalactic X-ray jets on kiloparsec scales, 2023, Nature Astronomy

Frequent co-authors collaborating with Nancy Reid include Yanbo Tang, Heather Battey, Yoav Benjamini, Richard D. De Veaux, and Bradley Efron. This network reflects interdisciplinary and methodological partnerships across their research interests.

Key venues where this scientist regularly publishes research are:

• arXiv (Cornell University)
• Harvard Data Science Review
• Statistica Sinica
• Journal of the Royal Statistical Society Series B (Statistical Methodology)
• Journal of the Royal Statistical Society Series A (Statistics in Society)

Main topics addressed in their research include statistical methods and inference, Bayesian inference, advanced statistical models, soil geostatistics and mapping, Markov chains and Monte Carlo methods, advanced statistical process monitoring, and data visualization and analytics.

• Statistical Methods and Inference
• Statistical Methods and Bayesian Inference
• Advanced Statistical Methods and Models
• Soil Geostatistics and Mapping
• Markov Chains and Monte Carlo Methods
• Advanced Statistical Process Monitoring
• Data Visualization and Analytics

The scientist's career includes recognition through several awards and honors. These include being a Fellow of the Royal Society in the United Kingdom (2018), a Member of the National Academy of Sciences (2016), Fellow of the American Association for the Advancement of Science (AAAS) since 2002, Fellow of the Royal Society of Canada with the Academy of Science citation (2001), recipient of the Wald Memorial Lectureship (2000), the COPSS Presidents' Award (1992), and Fellow of the American Statistical Association (ASA) since 1989.