Nancy Reid: 2022 COPSS Distinguished Lecturer
Rebecca W. Doerge, Carnegie Mellon University, is the COPSS Distinguished Achievement Award Committee Chair. Rebecca, together with Christian Genest and Erica E.M. Moodie, McGill University, writes:
The Committee of Presidents of Statistical Societies (COPSS) has selected Nancy Reid, OC, FRS, FRSC, Professor in the Department of Statistical Sciences at the University of Toronto, to give the Distinguished Achievement Award Lectureship at the 2022 Joint Statistical Meetings in Washington, DC. Her talk is tantalizingly entitled “Likelihood and its Discontents.”
Nancy Reid’s work has had major impact in the development of statistical theory. She has made unique contributions to the linking of modern themes and traditional concepts in statistical science. As noted by one of her supporters, “she has contributed fundamental and path-breaking work in a wide range of statistical problems, including nonparametric estimation for survival data, applications of differential geometry to statistics, conditional inference, profile and composite likelihood methods, higher order asymptotics, connections between Bayes and frequentist methods, and… the list goes on.” Reid’s work is wide-ranging and she has shown a striking aptitude for focusing on problems with a high practical impact and reward. The clarity of her writing and her attention to detail have also enhanced her lifetime interest in bringing statistical thinking to non-specialists.
Reid studied at the University of Waterloo (BMath 1974), the University of British Columbia (MSc 1976), Stanford University (PhD 1979), and Imperial College, London (PDF 1980). She joined the University of Toronto in 1986 from the University of British Columbia. She has held several leadership roles in statistical science, including Editor or Associate Editor for several leading journals, Chair of the Department (1997–2002), President of the Institute of Mathematical Statistics (1996–97), Vice President of the International Statistical Institute (1999–2001), President of the Statistical Society of Canada (2004–05), and Director of the Canadian Statistical Sciences Institute (2015–19).
Reid’s early research on bivariate influence functions and functional expansions provided theoretical and practical tools for the analysis of censored data. Her 1987 paper with the late Sir David Cox on orthogonal parameters and approximate conditional inference, read to the Royal Statistical Society, has been very influential. Her work has led to new approximation techniques and to a deeper understanding of the foundations of statistical inference. The author of numerous books and papers, she maintains an active research profile focused in part on the investigation of the relationship between significance functions and Bayesian posterior distributions, and generalized fiducial inference and inferential models.
Among her many awards, Reid was the first woman to receive the COPSS Presidents’ Award (1992), the first recipient of the Canadian Mathematical Society’s Krieger–Nelson Prize (1995), IMS Wald Lecturer in 2000, and the 2009 Gold Medalist of the Statistical Society of Canada. In 2016, the Royal Statistical Society awarded her the Guy Medal in Silver. [Reid has just been awarded the Guy Medal in Gold.]
Reid is a Fellow of the American Statistical Association, the Institute of Mathematical Statistics, and the American Association for the Advancement of Science. She is a corresponding Fellow of the Royal Society of Edinburgh, a Foreign Associate of the US National Academy of Sciences and, in 2015, she was appointed Officer of the Order of Canada. Her authoritative contributions to the theory of statistical inference, her commitment to excellence in statistical applications, and her outstanding service to the community make her a most apt recipient of the COPSS Distinguished Achievement Award and Lectureship.
COPSS Leadership Academy welcomes eight new members
The COPSS Leadership Academy recognizes early-career statistical scientists who show evidence of and potential for leadership and who will help shape and strengthen the field. Eight new members of the Academy have been announced. They are:
Xi Chen, New York University: For notable contributions to statistical inference for distributed, online, and high-dimensional data, to stochastic optimization, and to statistical applications in business domains, for outstanding educational efforts to the next generation of business leaders, and for significant industrial impacts.
Natalie Dean, Emory University: For ground-breaking, high-impact work in the development of innovative study designs and analyses for evaluating novel vaccines, and for wide-reaching public engagement and thought leadership during the COVID-19 pandemic.
Davina Durgana, Oxford University and Walk Free: In recognition of outstanding service through pioneering scientific research and policy communication to end human trafficking, and advocacy efforts to encourage youth and women in STEM fields across the world.
Philip Ernst, Rice University: For significant contributions of extraordinary merit to applied probability and mathematical statistics, particularly the resolution of the longstanding conjecture of Yules’ nonsense correlation, outstanding teaching and leadership.
Pierre Jacob, ESSEC Business School: For path-breaking contributions to Monte Carlo algorithms and Bayesian statistics, and for exemplary dedication as teacher and mentor.
Kristian Lum, Twitter: For strong contributions to the study of algorithmic fairness and ethics in statistics and data science; for high-quality, high-impact collaboration and advocacy in social justice; and for leadership in maximizing our profession’s openness and support of all members.
Lester Mackey, Microsoft Research: For significant contributions to the theory and practice of statistical machine learning.
Betsy Ogburn, John Hopkins Bloomberg School of Public Health: For creative methodological innovations in causal and network analysis; for contributions to education; for generous service to the profession and society, including leadership in addressing the COVID-19 pandemic.
2022 Elizabeth L. Scott Award and Lectureship: Madhu Mazumdar
The COPSS 2022 Elizabeth L. Scott Award and Lectureship recipient is Madhu Mazumdar, Director of the Institute for Healthcare Delivery Science at the Mount Sinai Health System and is a Professor of Biostatistics at the Center of Biostatistics, Department of Population Health Science and Policy.
Madhu Mazumdar developed methodologies for detecting publication bias in meta-analysis; for adjusting selection bias in clinical trials; for allowing interim looks at data in clinical trials comparing diagnostic tests; for developing and validating quality of life questionnaire; and for estimating misclassification rate of responders when oncologic response criteria were changed. Her collaborative research resulted in personalized treatment regimen for various cancer types and orthopedic surgeries. Her work also changed guidelines for staging cancer and practice guidelines for use of anesthetics. She developed innovative interdisciplinary educational and research programs, in collaboration with various clinical departments that increased productivity through grantsmanship and augmented clinical revenue through improved care delivery.
Dr. Mazumdar’s Scott lecture is titled “Biostatistical methods and team science: Generating evidence for optimization of clinical practice”. She will speak on innovative statistical applications to catalyze healthcare delivery, addressing two specific challenges facing US healthcare: 1) how to choose patients for knee-replacement surgery who will benefit most in terms of their quality of life and what is the cost-effectiveness of this procedure? and 2) how to improve quality of cancer care through modelling of incurred cost? Dr. Mazumdar will highlight the critical role of statistical methods in answering these questions and will illustrate how collaborations, guided with principles of team science, provide opportunities for practicing leadership, embracing diversity, managing conflict, and sharing credit.