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COPSS Distinguished Achievement Award and Lectureship

Most Recent Winner About the Award Current Committee Operating Procedure Past Recipients

Most Recent Winner

2024 Lecturer

Robert Tibshirani, Stanford University

For fundamental contributions to statistics and machine learning that have deepened, broadened and created a bridge between those fields; for bringing key statistical ideas in multiple testing and high-dimensional learning to the broader scientific community; for high-impact textbooks on generalized additive models, the bootstrap, high dimensional statistics, and statistical learning that have come to define those fields; and for outstanding mentoring of PhD students and junior researchers.

Dr. Tibshirani's talk is entitled "Pre-Training and the Lasso."

Abstract

Pretraining is a popular and powerful paradigm in machine learning, in which a neural network is fit to a large dataset (for example hundreds of image classes) and then fine-tuned for a more specific task --such as classifying dogs from cats. In this paper, we ask the question Can pretraining help the lasso?''. We develop a framework for the lasso in which an overall model is fit to a large set of data, and then fine-tuned to a specific task on a smaller dataset. This latter dataset can be a subset of the original dataset, but does not need to be. We find that this framework has a wide variety of applications, including stratified models, multinomial targets, multi-response models, conditional average treatment estimation and even gradient boosting. In the stratified model setting, the pretrained lasso pipeline estimates the coefficients common to all groups at the first stage, and then group-specific coefficients at the second fine-tuning'' stage. We show that under appropriate assumptions, the support recovery rate of the common coefficients is superior to that of the usual lasso trained only on individual groups.

Biography of Dr. Tibshirani

Robert Tibshirani is a Professor of Biomedical Data Science and statistics at Stanford University. He has made important contributions to the statistical analysis of complex datasets. Some of his most well-known contributions are the Lasso, which uses L1 penalization in regression and related problems, generalized additive models, and Significance Analysis of Microarrays (SAM). He also co-authored five widely used books ‘Generalized Additive Models’, ‘An Introduction to the Bootstrap’, ‘The Elements of Statistical Learning’, "An Introduction to Statistical learning", and ‘Sparsity in Statistics: the Lasso and its generalizations’. He is an active collaborator with many scientists at Stanford Medical school.

Tibshirani received the COPSS Presidents' Award in 1996. Given jointly by the world's leading statistical societies, the award recognizes outstanding contributions to statistics by a statistician under the age of 40. He was elected a Fellow of the Royal Society of Canada in 2001, the National Academy of Sciences in 2012, and the Royal Society of Britain in 2019. In 2021 he received the ISI Founders of Statistics Prize for his 1996 paper Regression Shrinkage and Selection via the Lasso.

About the Award

The COPSS Distinguished Achievement Award and Lectureship was formerly known as the R. A. Fisher Award and Lectureship; it was renamed in 2020. The Award and Lectureship is a very high recognition of meritorious achievement and scholarship in statistical science and recognizes highly significant impact of statistical methods on scientific investigations. The award winner will receive a plaque and a cash honorarium of $2,000, and deliver the COPSS Distinguished Lecture at the Joint Statistical Meetings.

Award Committee (2024-2025)

Scott Holan	ASA	Oct 2023 - Sept 2026	holans@missouri.edu
Limin Peng	COPSS	Oct 2022 - Sept 2025	lpeng@emory.edu
Dean Follmann	ENAR	Oct 2023 - Sept 2027	dfollmann@niaid.nih.gov
Chris Holmes	IMS	Oct 2023 - Sept 2026	chris.holmes@stat.ox.ac.uk
Lisa Lix (Chair)	SSC	Oct 2022 - Sept 2025	lisa.lix@umanitoba.ca
Elizabeth Juarez-Colunga	WNAR	Oct 2024 - Sept 2027	elizabeth.juarez-colunga@cuanschutz.edu
Wing Wong	2020 Awardee	Oct 2023 - Sept 2024	whwong@stanford.edu

Purpose and History

The Distinguished Achievement Award and Lectureship (DAAL) is given yearly to an individual in recognition of outstanding contributions to statistical methods that have had significant impact on scientific investigations. This award was formerly known as the RA Fisher Lectureship award from 1963-2019.

Award Committee

The Award Committee selecting the recipient will consist of six members. Each of the five charter member societies (i.e., ASA, ENAR, WNAR, IMS, and SSC), plus the COPSS Chair, appoints one committee member. These six committee members serve for a three-year term on a rotating basis. The award winner from 6 years previous to the current award is invited by the COPSS Chair to serve as the seventh committee member. His/her term is for one year. In the event that this Award winner is unable (or unwilling) to serve on this committee or is already on the committee, the award winner in the subsequent year will be invited by the Chair to serve and this person then serves for two years. For example, for the 2016 award, the 2010 awardee serves as the seventh member. If he/she cannot serve, the 2011 awardee will be invited to serve. The COPSS Chair appoints the chair of the award committee. Two new members, including the past awardee, are appointed per year.

Frequency of Award

The award shall be given every year if, in the opinion of the Award Committee, an eligible and worthy nominee is found. The Award Committee shall have the option of not giving an award for any year. The Award Committee may not split the award between more than one winner.

Nominations and Eligibility

The award is open to all regardless of age, race, gender, sexual orientation, nationality or citizenship. Nominees must be living at the time of their nomination. Nomination submissions will be invited by October of the previous year and will close on December 15th. Prior nomination does not exclude a nominee from consideration in subsequent years. No member of the Award Committee, the officer of COPSS, or societal member of COPSS shall be eligible to receive the award during his or her term of service.

Eligible candidates are expected to adhere to the highest standards of statistical practice, professional conduct, and personal conduct; see the Ethical Guidelines for Statistical Practice published by the Committee on Professional Ethics of the American Statistical Association: https://www.amstat.org/ASA/Your-Career/Ethical-Guidelines-for-Statistical-Practice.aspx for more information.

Eligible nominations should be sent to the Chair of the COPSS Distinguished Achievement Award and Lectureship Committee in PDF and should include a nomination letter, the candidate’s curriculum vitae and contact information, and three support letters. Award Committee members should not prepare individual nominations or letters of support.

Selection Criteria

The criteria are outstanding contributions to statistical methods that have had significant impact on scientific investigations.

The Award Committee is responsible for the review of selection criteria and can recommend any modifications to COPSS.

Form and Presentation of Award

The award consists of a plaque, a citation, and a cash honorarium of $2,000. It is presented at the COPSS Awards and Lecture session at the Joint Statistical Meetings (JSM), usually on Wednesday at 4:00 p.m. local time. Reimbursement for reasonable travel and hotel expenses to attend the JSM to receive the award is provided to the recipient, if other funds are unavailable. The COPSS Distinguished Lecture is generally 1 hour long with ample additional time for questions and discussion.

Important Dates

Members of the Award Committee will be appointed by September 30th of the previous year. Chair of COPSS will work with COPSS members to complete all committee appointments. Chair of COPSS will select the Award Committee chair. If any COPSS member society is unable to appoint their member by October 1st of the previous year, the Award Committee will proceed and complete its work without representation of that society.
Award recipient will be selected and notified by January 15th of the award year.
Chair of the Award Committee will work with the Secretary/Treasurer of COPSS to provide all the necessary information to the ASA/JSM Awards Coordinator by February 1st of the award year.

Committee Chair Responsibilities

Communicate the award criteria and selection process to Committee members.
Contact and encourage unsuccessful nominations from the previous award period to be updated and renominated. (COPSS Secretary should have previous unsuccessful nominations).
Organize and chair Committee discussion of nominees and selection of award recipient.
Inform the Award recipient of their selection by February 1st.
Inform all other nominators that a selection has been made.
Prepare the award citation.
Convey the award recipient’s name, contact information, citation, picture, and other relevant information to the COPSS Secretary/Treasurer by February 1st for preparing the article for publication and plaque.
Prepare presentation slides for the COPSS Awards Presentation at the JSM.
Introduce award and recipient at COPSS Awards Presentation at the JSM.
Send a complete list of unsuccessful nominations to COPSS Secretary for future re-nomination.
Communicate any recommendations for changes to any part of this document to the COPSS Chair and Secretary/Treasurer.

Committee Member Responsibilities

Work with the chair to adhere to the selection timeline.
Participate fairly and openly in the selection deliberations.
Request removal from the committee if other time constraints do not allow for adequate attention to the nominations and award process.

COPSS Secretary/Treasurer Responsibilities

Review and manage the expenditure of the Award Endowment Fund
Assist Committee Chair in correspondence, as needed.
Prepare articles about the award recipient for publication in AmStat News and IMS Bulletin and provide them to ASA Meetings department ASSA/JSM and IMS award coordinator by March 31st.
Prepare plaques and checks for presentation at the JSM.
Assist the COPSS Chair in preparing presentation.
Prepare financial reports for the committee meeting at JSM.
Coordinate with Committee Chair and ASA staff on Awards presentation
Prepare a report of the award ceremony for AmStat news and IMS Bulletin by August 31st.
Prepare a call for nominations for the following year’s awards for publication in AmStat news and IMS Bulletin by August 31st.

COPSS Chair Responsibilities

Ensure that COPSS member societies name Award Committee members by August 1st of the previous year.
Select Award Committee Chair by August 31st of the previous year.
Help to orient committee members and the Award Committee Chair to their responsibilities.
Review potential conflicts of interest and other issues for the Committee Chair, if they arise.
Thank committee members and the Award Committee Chair to their responsibilities and solicit suggested improvements to the award process after the award cycle is completed.

Past Recipients of the Award (formerly known as the R.A. Fisher Award and Lectureship)


1964	S. Bartlett University of Chicago and University College, London	“R. A. Fisher and the last fifty years of statistical methodology” (JASA 60, 1965, 395-409)
1965	Oscar Kempthorne Iowa State University	“Some aspects of experimental inference” (JASA 61, 1966, 11-34)
1966	None
1967	John W. Tukey Princeton University and Bell Telephone Laboratories	“Some perspectives in data analysis”
1968	Leo A. Goodman University of Chicago	“The analysis of cross-classified data: independence, quasi-independence, and interactions in contingency tables with or without missing entries” (JASA 63, 1968, 1091-1131)
1969	None
1970	Leonard J. Savage Princeton University	“On rereading R. A. Fisher” (Annals of Statistics 4, 1976, 441-500)
1971	Cuthbert Daniel Private Consultant	“One-at-a-time plans” ( JASA 68, 1973, 353-360)
1972	William G. Cochran Harvard University	“Experiments for nonlinear functions” ( JASA 68, 1973, 771-781)
1973	Jerome Cornfield George Washington University	“On making sense of data”
1974	George E. P. Box University of Wisconsin	“Science and statistics” (JASA 71, 1976, 791-799)
1975	Herman Chernoff Massachusetts Institute of Technology	“Identifying an unknown member of a large population” (Annals of Statistics 8, 1980, 1179-1197)
1976	George A. Barnard University of Waterloo	“Robustness and the logic of pivotal inference”
1977	R. C. Bose University of North Carolina, Chapel Hill	“R. A. Fisher's contribution to multivariate analysis and design of experiments” (Early history of multivariate statistical analysis. Multivariate Analysis IV, Proc. Fourth International Symposium, Dayton, Ohio, 1977.)
1978	William Kruskal University of Chicago	“Statistics in society: problems unsolved and unformulated”
1979	C. R. Rao Pennsylvania State University	“Fisher efficiency and estimation of several parameters”
1980	None
1981	None
1982	F. J. Anscombe Yale University	“How much to look at the data” (Utilitas Mathematica 21A, 1982, 23-28)
1983	I. R. Savage University of Minnesota	“Nonparametric statistics and a microcosm”
1984	None
1985	T. W. Anderson Stanford University	“R. A. Fisher and multivariate analysis”
1986	David H. Blackwell University of California, Berkeley	“Likelihood and sufficiency”
1987	Frederick Mosteller Harvard University	Methods for studying coincidences” (with P. Diaconis) (JASA 84, 1989, 853-861)
1988	Erich L. Lehmann University of California, Berkeley	“Model specification: Fisher's views and some later strategies”
1989	Sir David R. Cox Nuffield College, Oxford	“Probability models: their role in statistical analysis
1990	Donald A. S. Fraser York University	“Statistical inference: likelihood to significance” (JASA 86, 1991, 258-265)
1991	David R. Brillinger University of California	“Nerve cell spike train data analysis: a progression of technique” (JASA 87, 1992, 260-271)
1992	Paul Meier Columbia University	“The scope of general estimation”
1993	Herbert E. Robbins Columbia University	“N and n - sequential choice between two treatments”
1994	Elizabeth A. Thompson University of Washington	“Likelihood and linkage: from Fisher to the future”
1995	Norman E. Breslow University of Washington	“Statistics in epidemiology: the case-control study"
1996	Bradley Efron Stanford University	“R. A. Fisher in the 21st Century”
1997	Colin L. Mallows AT&T Bell Laboratories	“The Zeroth Problem”
1998	Arthur Dempster Harvard University	“Logistic Statistics: Modeling and Inference”
1999	Jack D. Kalbfleisch University of Waterloo	"The Estimating Function Bootstrap" (Canadian Journal of Statistics, 30, 2000, 449-499)
2000	Ingram Olkin Stanford University	"R. A. Fisher and the Combining of Evidence"
2001	James O. Berger Duke University	"Could Fisher, Jeffreys, and Neyman have agreed on Testing?"
2002	Raymond Carroll Texas A&M University	"Variability Is Not Always A Nuisance Parameter"
2003	Adrian F. M. Smith University of London	"On Rereading L. J. Savage Rereading R. A. Fisher"
2004	Donald B. Rubin Harvard University and University of Wisconsin	"Causal Inference Using Potential Outcomes: Design, Modeling, Decisions" For fundamental and innovative contributions to scientific investigation through the development and promotion of modern statistical methodologies including missing data methods, causal inference, the EM algorithm and multiple imputations, and for his considerable impact on applied data analysis and Bayesian statistics.
2005	R. Dennis Cook University of Minnesota	“Dimension Reduction in Regression” (Statistical Science, 22, 2007, 1-26) For fundamental contributions to statistical analysis through his revolutionary research in the field of regression analysis that has led to numerous methodological contributions and innovations including influence statistics and regression graphics.
2006	Terence P. Speed University of California, Berkeley and Walter & Eliza Hall Institute of Medical Research	“Recombination and Linkage” For his fundamental contributions to the field, spanning early work on spatial models and contingency tables, through his contributions to classical ANOVA, to his innovative research in statistical genetics and genomics, through which Professor Speed has profoundly influenced the theory and practice of statistical science.
2007	Marvin Zelen Harvard School of Public Health	“The early detection of disease – Statistical challenges” For fundamental contributions to the development of biostatistical science, which have had huge and lasting impact on the design, implementation and analysis of clinical trials; and for his vision and leadership that have established biostatistics as a central discipline in modern biomedicine and public health in the US and around the world.
2008	Ross L. Prentice Fred Hutchinson Cancer Research Center and University of Washington	“The Population Science Research Agenda: Multivariate Failure Time Data Analysis Methods.” For fundamental contributions to the theory and practice of statistical science; for his influential and innovative research in the areas of survival analysis, life history processes, case-control cohort studies; and for his influential role in the conception, design, and implementation of the Women’s Health Initiative.
2009	Noel Cressie Ohio State University	“Where, When, and then Why.” For pioneering advances in statistical methodology inspired by science and engineering, particularly in the areas of spatial and spatio-temporal statistics; and for his vision and leadership in the statistical modeling of uncertainties in environmental science.
2010	Bruce G. Lindsay Pennsylvania State University	“Likelihood: Efficiency and Deficiency.” For fundamental contributions to statistical theory that have had a profound impact on the practice of statistics; this includes significant results on mixture models, conditional score functions and composite likelihood that have influenced later developments in measurement error models and spatial statistics among other areas.
2011	C.F. Jeff Wu Georgia Institute of Technology	“Post-Fisherian Experimentation: from Physical to Virtual” For fundamental contributions to the planning, analysis and interpretation of statistical studies that have had a profound impact on the practice of statistics, especially in engineering; this includes significant results on resampling methods, theory of experimental design and pioneering work in industrial statistics that have changed the way statistical studies are used to optimize products and processes.
2012	Roderick J. Little University of Michigan	“In praise of simplicity not mathematistry! Simple powerful ideas for the statistical scientist” For outstanding statistical research in the modeling and evaluation of missing data, sample survey and causal inference; for the clear and comprehensive application of these and other methodologies in science and public policy arenas; and for diverse and effective professional and academic leadership contributions
2013	Peter J. Bickel University of California, Berkeley	"Big Data: Continuities and Discontinuities” For groundbreaking contributions to semiparametric and nonparametric methods, adaptive estimation, and robust statistics; for applying in-depth and intricate theoretical analysis to realistic problems in the biological sciences; for penetrating and insightful analysis of scientific methodology which has yielded a lasting impact on our understanding of both theory and methods; and for exceptional training and mentoring of students, leadership of professional societies, and leadership of his academic department.
2014	Grace Wahba University of Wisconsin-Madison	“Positive Definite Functions, Reproducing Kernel Hilbert Spaces, and All That” For fundamental contributions to many areas of statistics, including time series, splines, smoothing, nonparametric statistics, likelihood estimation, density estimation, and to interdisciplinary areas including climatology, epidemiology, bioinformatics and machine learning. In particular, her work in reproducing kernel Hilbert space representation and generalized cross-validation have become standard practice in scientific research and industry.
2015	Stephen E. Fienberg Carnegie Mellon University	“R. A. Fisher and the Statistical ABCs" For wide-ranging and highly influential contributions to the theory and practice of statistics; for fundamental advances in methodology, interpretation and computation in the analysis of categorical data; for broad-reaching contributions to statistical methods for sample surveys; for seminal work on record linkage, privacy and social network analysis; for outstanding and prolific service to the profession and to society; and for being a role model, advocate and mentor to young statisticians.
2016	Alice S. Whittemore Stanford University School of Medicine	“Personalizing Disease Prevention: Statistical Challenges” For fundamental contributions to biostatistics and epidemiology, covering a wide range of topics from environmental risk assessment to genetic linkage analysis, genetic association studies and cancer epidemiology; for bringing her statistical and mathematical insight to bear on the collection and interpretation of scientific data; for her leadership in large consortia of cancer studies; and for being a role model for many young scientists.
2017	Robert E. Kass Carnegie Mellon University	“The Importance of Statistics: Lessons from the Brain Sciences” For ground breaking contributions to several areas of statistics including use of differential geometry in statistical theory as well as theory and methodology of Bayesian inference; for strong commitment to the application of principled statistical thinking and modeling to problems in computational neuroscience; and for his strong dedication to training of students and users of statistics.
2018	Susan A. Murphy Harvard University	“The Future: Stratified Micro-randomized Trials with Applications in Mobile Health” For scientific contributions to statistical theory and methods at the highest level and for fundamental advances in the innovative use of statistics to further behavioral and mental health research.
2019	Paul R. Rosenbaum University of Pennsylvania	“An Observational Study Used to Illustrate Methodology for Such Studies” For pioneering contributions to statistical methodology for observational studies, important applications of such methodology to health outcomes studies, lucid books on statistical principles and methodology for observational studies and excellent mentoring.
2020	Kathryn Roeder Carnegie Mellon University	“Statistics and Genetics Offer a Window into Autism” For outstanding contributions to statistical science in the areas of mixture models, semiparametric inference, and multiple testing, and to the development of statistical methods aimed at finding the genetic basis of human disease, including the development of powerful methods for discovering genes underlying psychiatric disorders such as autism.
2021	Wing Hung Wong Stanford University	“Understanding human trait variation from the gene regulatory systems perspective” For seminal and consequential advancements in the theoretical and methodological underpinnings of Bayesian modeling and inference; for significant contributions in high-dimensional statistical inference, nonparametric Bayesian modeling, and their wide-ranging applications in biomedical and natural science.
2022	Nancy Reid University of Toronto	"Likelihood and Its Discontents" For pioneering contributions to statistical theory and in particular to likelihood inference, strong commitment to the promotion of statistical thinking across a range of applications, outstanding service to the statistical profession, and for being a role model, advocate and mentor to young statisticians.
2023	Bin Yu University of California, Berkeley	"Veridical Data Sciences towards Trustworthy AI" For fundamental contributions to information theory; statistical and machine learning methodology; interdisplinary research in fields such as genomics, neuroscience, remote sensing, and document summarization; and for outstanding dedication to professional service, leadership, and mentoring of students and young scholars.
2024	Robert Tibshirani Stanford University	"Pre-Training and the Lasso" For fundamental contributions to statistics and machine learning that have deepened, broadened and created a bridge between those fields; for bringing key statistical ideas in multiple testing and high-dimensional learning to the broader scientific community; for high-impact textbooks on generalized additive models, the bootstrap, high dimensional statistics, and statistical learning that have come to define those fields; and for outstanding mentoring of PhD students and junior researchers.