Professor Jiahua Chen holds a Tier 1 Canada Research Chair in the Department of Statistics at the University of British Columbia. Jiahua was born in China where the Cultural Revolution resulted in his not receiving a regular elementary education nor a complete high school education. In fact, he worked full time on construction sites for three years when he should have been attending high school. Nonetheless, he remarkably gained entrance to the University of Science and Technology of China at Hefei, where he earned an undergraduate degree in mathematics in 1982 followed by a Masters degree in statistics from Academia Sinica in Beijing in 1985. He completed his PhD under Professor C. F. Jeff Wu at the University of Wisconsin in 1990 and was a postdoctoral fellow under Professor Jack Kalbfleisch. In 1991, he joined the University of Waterloo as Assistant Professor and was promoted to Associate Professor and Professor in 1996 and 2001, respectively. In 2007 he took up a professorial appointment and his Research Chair at the University of British Columbia.
Jiahua has made outstanding research contributions in many areas of statistics including experimental design, sampling theory, empirical likelihood, mixture models and applications in genetics. In addition, he has served the Canadian and international statistical communities exceptionally well, for example, as Editor of The Canadian Journal of Statistics and President of the International Chinese Statistical Association. He has a tremendous record as educator, having supervised many PhD and Master’s students; many of his PhD advisees are now active researchers and teachers at Canadian and other universities.
In his PhD thesis, Jiahua used Hadamard matrix representations to identify isomorphisms among 2-level fractional factorial designs and to develop a systematic method for obtaining optimal designs. The resulting papers, published in the Annals of Statistics, have been widely cited and influential. This research has been extended in various directions in recent years and represents first-rate results in a forefront area.
Survey sampling is a second area of outstanding contribution. His work on nearest neighbor imputation for non-response in survey data has been very widely cited. In two papers with Jun Shao, in particular, he addresses a longstanding problem of assessing accuracy of estimates; they develop a cohesive theory and establish the theoretical validity of the methods. This work is widely recognized by survey sampling methodologists and was identified as a development of fundamental importance by W. Fuller in the International Conference on Recent Advances in Survey Sampling held in 2002. Related to the work on sample surveys is a very influential contribution to the theory and application of empirical likelihood. Jiahua’s work with Jing Qin and others has developed empirical likelihood in the context of finite populations. The fundamental 1993 Biometrika paper is widely cited and has formed the basis of much additional work. He and others are still developing the consequences and extensions of this work. Jiahua, in particular, has an important paper on nonparametric confidence intervals in The Canadian Journal of Statistics (Chen, Chen and Rao, 2003).
Jiahua also has an outstanding and ongoing series of contributions to the literature on mixture models. His 1995 Annals of Statistics paper on optimal rates of convergence for estimating mixture models was innovative and is widely cited. Subsequent to this, he has examined the limiting distribution of the likelihood ratio statistic in a variety of settings and extended and refined many results in the literature. More recently, he has been examining and developing methods for testing the order of a mixture. Such problems arise naturally in statistical genetics and this work is receiving attention among researchers there. His work on the asymptotic distribution of the likelihood ratio statistic for testing homogeneity versus a two-component normal mixture with common variance is a tour de force of mixture model asymptotics and yields an interesting and unusual result. Asymptotic results for likelihood ratio statistics tend to be very complicated and Jiahua and co-authors have developed his idea of modified or penalized likelihood methods. This approach restores a degree of regularity to the problem, and leads to relatively much simpler asymptotic results and easy to implement procedures. This has resulted in a number of publications in The Canadian Journal of Statistics (Chen, 1998), Journal of the Royal Statistical Society, Journal of the Royal Statistical Society: Series B (Statistical Methodology) (Chen, Chen and Kalbfleisch, 2001, 2004), Statistica Sinica (Chen and Chen, 2003; Fu, Chen and Kalbfleisch, 2009), and the Journal of Statistical Planning and Inference (Chen and Kalbfleisch, 2005).
More recently Jiahua has focused energies on the general research areas of the Canada Research Chair in Application of Finite Mixture Models in Statistical Genetics. He has continued his work on estimating the order of a finite mixture model in several excellent papers, most recently in a wide-ranging paper in the Annals of Statistics (Chen and Li, 2009), Journal of the American Statistical Association (Li and Chen, 2010; Chen, Li and Fu, 2012). In addition, his Biometrika paper (Chen and Chen, 2008) makes an important contribution to extending the Bayesian Information Criterion to problems in high dimensions as arise in high throughput applications in genetics and elsewhere. This work has already received many citations. He has continued his work on empirical likelihood with important results that extend the method to problems with constraints.
Jiahua’s contributions have been recognized before. He was elected Fellow of the Institute of Mathematical Statistics in 2005 and of the American Statistical Association in 2009. Also in 2005 he was awarded the CRM-SSC Prize for outstanding contributions to the statistical sciences. In 2007 he was awarded the Canada Research Chair, Tier I, which has recently been renewed. In addition he has won university research awards at both the University of Waterloo and the University of British Columbia.
Professor Mary Thompson is the recipient of the 2014 Distinguished Service Award from the Statistical Society of Canada. This award honours an individual who has played an important and substantial role in fostering growth and success of the Canadian Statistical Sciences community through leadership in the SSC. Mary’s many years of strong and effective leadership have greatly benefited our society and this award is a fitting recognition for her commitment to our discipline and profession.
Mary obtained her undergraduate degree in Mathematics at the University of Toronto and her Master’s and doctorate at the University of Illinois. Upon completing her graduate studies Mary was appointed at the University of Waterloo where she spent the balance of her career. She is currently Distinguished Professor Emerita in the Department of Statistics and Actuarial Science.
Mary’s statistical research has included the development of estimating function theory, the foundations of survey methodology, applied probability and biostatistics, and her contributions have been highly influential. In addition to advancing statistical theory and methods, Mary has a commitment to addressing important societal issues through public policy and health research. She continues to play an important role in the International Tobacco Control Study, a global longitudinal study examining the effect of government policy on smoking behaviour in over 20 countries. In 2010 Mary and her collaborators Geoffrey Fong and David Hammond were among the first to receive a Top Canadian Achievement in Health Research Award from the Canadian Institutes of Health Research (CIHR) and the Canadian Medical Association Journal. She is recipient of the Gold Medal of the SSC (2003), Fellow of the American Statistical Association (1985), Fellow of the Institute of Mathematical Statistics (1998), and Fellow of the Royal Society of Canada (2006).
Mary has an outstanding record of leadership at the University of Waterloo, having held the position of Chair of the Department of Statistics and Actuarial Science (1996-2000), Associate Dean (1988-1991), and Acting Dean (2001). She was also instrumental in the formation of the University of Waterloo’s Survey Research Centre, for which she served as co-Director from 1999 to 2013. She has supervised more than 25 PhD students and numerous Master’s students, and in 2007 she received the Award of Excellence in Graduate Supervision from the University.
Within the Statistical Society of Canada, Mary served in many capacities including the Finance Committee (1987-89), the Awards Committee (1989-92), the Editorial Board of The Canadian Journal of Statistics (1992-95), and the Research Committee (1993-2000). Her leadership positions have included Treasurer (1985-87), President of the Survey Methods Section (1993-94), and President of the SSC (2003-04). Mary also served on the NSERC Statistical Sciences Grant Selection Committee (1992-95; Chair 1994-95) as well as the Steering Committee for the NSERC Reallocation Brief (1996-98).
Throughout her career Mary has demonstrated a commitment to equity and diversity in academia through serving on or chairing Advisory Committees at the University of Waterloo such as the Women in Mathematics Committee (1975-77, 1993-95) and the Female Faculty Recruitment Committee (2002) as well as the Committee on Women in Statistics (1977, 1981-84) of the American Statistical Association. In 2010 she received the Committee of Presidents of Statistical Societies Elizabeth L. Scott Award in recognition of her efforts to further the careers of women in academia.
Most recently, Mary’s thoughtful and effective leadership as Chair of the Canadian Statistical Institute Development Committee (CSIDC) was instrumental in establishing a framework for a major initiative recommended in the NSERC Long Range Plan for Mathematical and Statistical Sciences, having joint sponsorship from the Fields Institute, the Pacific Institute for Mathematical Sciences, and the Centre de recherches mathématiques. These funds have helped strengthen the position of the Statistical Sciences in Canada by the establishment of the Canadian Statistical Sciences Institute (CANSSI), a national institute with the mandate of advancing research in the statistical sciences and promoting the discipline. Mary has served as the Scientific Director since its inception in 2012.
Leadership takes many forms and the examples above are a tangible reflection of traditional measures. In addition, however, Mary leads by example, as a thoughtful and balanced administrator, influential and dedicated researcher, and a talented and supportive mentor. She is an exceptional role model in the many facets of her career and, as a community, we are extremely fortunate to have benefited from her leadership in the Statistical Society of Canada over these many years.
The citation for the award reads:
“To Mary Thompson, for important contributions to the SSC and the Canadian statistics community, notably as President and Treasurer of SSC, President of the Survey Methods Section of SSC, Founding Scientific Director of CANSSI, Chair of the Canadian Statistical Institute Development Committee, Chair of the NSERC Statistical Sciences Grant Selection Committee, member of the Statistics Canada Advisory Committee on Statistical Methods, member of the Editorial Boards of CJS and Liaison, and a career of leadership and innovation in statistical research and training.”
Pierre Robillard Award
Pierre Robillard Award: Liqun Diao
Liqun Diao is the winner of the 2013 Pierre Robillard Award of the Statistical Society of Canada. This prize recognizes the best PhD thesis in probability or statistics defended at a Canadian university in a given year.
Liqun’s thesis is entitled “Copula Models for Multi-type Life History Processes.”It was written at the University of Waterloo under the supervision of Richard Cook.
Liqun’s PhD work focused on the modeling and analysis of multifaceted life history processes. Liqun was devoted to developing innovative statistical models that have appealing marginal properties and convenient parameterizations of association. She tackled different statistical issues in the field of life history analysis including marked point processes, multiple multistate processes and bivariate survival data under right-censored or current status observation schemes. The techniques used to handle the complex dependence structures have a common theme in which multivariate density decomposition and dependence structure are modeled through copula functions. Robust estimation and model misspecification are also part of an underlying theme of this research.
Liqun was born in Jilin, China. She received her Bachelor of Economics in Statistics from the Renmin University of China in 2007. After completing her Master of Mathematics in Statistics - Biostatistics at the University of Waterloo in 2009, Liqun stayed on to join the doctoral program and defended her PhD thesis in August 2013. Liqun is currently working as a Postdoctoral Associate in the Department of Biostatistics and Computational Biology at the University of Rochester. Her postdoctoral work is to develop novel statistical methods for building, selecting and evaluating clinically relevant risk indices using recursive partitioning methods and other techniques from machine learning.
The criteria used in selecting the winner of the Pierre Robillard Award include the originality of ideas and techniques, the possible applications and their treatment, and the potential impact of the work. The award is named in memory of Professor Pierre Robillard, an outstanding dynamic young statistician at the Université de Montréal, whose untimely death in 1975 cut short what promised to be a highly distinguished career.
Liqun Diao will present the results of her thesis in a special session at the 42nd Annual Meeting of the Statistical Society of Canada to be held in Toronto, Ontario, May 25 to 28, 2014.
CRM-SSC Prize in Statistics
CRM-SSC Prize in Statistics: Fang Yao
The CRM-SSC Prize in statistics is awarded annually by the Centre de recherches mathématiques (Montréal) and the Statistical Society of Canada to recognize a statistical scientist's professional accomplishments in research during the first fifteen years after earning a doctorate. This year's winner is Fang Yao of the University of Toronto.
Fang Yao has conducted his most important research since arriving at the University of Toronto in 2006; it is both seminal and beautiful.
Fang received his Bachelors degree from the University of Science and Technology in China. He was admitted to the University of California, Davis, for graduate studies, where he completed both his MSc and his PhD in three years. His doctoral dissertation was completed under the joint supervision of Hans-Georg Müller and Jane-Ling Wang. The dissertation was novel for coupling advanced methodological machinery with a data-type critical for establishing causal relationships. Subsequent to completing his degree in 2003, Fang assumed a position in the Department of Statistics at Colorado State University. The Department of Statistical Sciences at the University of Toronto successfully recruited Fang in 2006; he was subsequently promoted to the rank of Associate Professor with tenure in 2008. During his first sabbatical, Fang was invited to the Statistical and Applied Mathematical Sciences Institute in North Carolina as a Research Fellow, where he gave the opening address for a thematic program and subsequently led one of the working groups during the fall term. He then moved on to UBC for the rest of his sabbatical leave, where he created a new advanced graduate course, Topics in Smoothing: Functional Data Analysis.
Fang’s expertise is in the area of functional data analysis (FDA), a relatively new field in statistical science that regards data as a set of functions. Fang’s contributions to FDA have been fundamental. His research program, characterized by great ambition and breadth, continues to lay the foundations of FDA by framing it in terms of interpretable models with complex correlation structures that improve the efficiency of inference techniques. Methods he develops are useful for both representation and regression problems, and are accessible through the development of his publicly available software PACE, which has significantly extended the impact of his research in statistical science and other fields. Fang is the consummate statistician, having a deep understanding of rigorous mathematical techniques, a broad statistical knowledge and the ability to apply both in substantive problems.
Fang Yao has 30 peer-reviewed publications and is highly cited. His NSERC Discovery grant increased substantially when it was renewed, and was coupled with a Discovery Accelerator Supplement. Fang has made considerable contributions to the profession, particularly in supporting the development of research through his involvement in the organization of workshops, conferences and programs and through his commitment to the review of scholarly work. Fang is an Associate Editor for eight journals, including the Journal of the American Statistical Association, the Annals of Statistics and the Canadian Journal of Statistics.
Fang and his wife, Helen, were extremely excited to celebrate the arrival of their first child, Alexander, in the summer of 2013. Fang enjoys outdoor activities, such as skiing, hiking and rock climbing, having been introduced to them in Colorado and California. He also likes playing poker with friends and in local tournaments.
Fang Yao will present an overview of his work in a special session at the 42nd Annual Meeting of the Statistical Society of Canada to be held in Toronto, Ontario, May 25 to 28, 2014.
The citation for the prize reads:
“To Fang Yao, for his foundational, influential and trail-blazing research in the field of functional data analysis; for exploring fruitful connections between longitudinal and functional data, and for demonstrating ways in which tools from the more traditional fields of nonparametric statistics can be successfully leveraged in FDA research.”
The Canadian Journal of Statistics Award
The Canadian Journal of Statistics Award: Art Owen
The Canadian Journal of Statistics Award is presented each year by the Statistical Society of Canada to the author(s) of an article published in the Journal, in recognition of the outstanding quality of the paper’s methodological innovation and presentation. This year’s winner is the article entitled “Self-concordance for empirical likelihood” (Volume 41, no. 3, pp. 387-397) by Art B. Owen.
Empirical likelihood provides likelihood-based confidence regions and tests without requiring the user to know a parametric family generating the data. The computation of the empirical likelihood ratio function for the mean reduces to a convex optimization. This paper reformulates empirical likelihood optimization as the minimization of a self-concordant convex function. Under self-concordance there is a mathematical guarantee of convergence for Newton iterations with backtracking. Art Owen is a professor of Statistics at Stanford University. He holds a Bachelor of Mathematics from the University of Waterloo, and a PhD in Statistics from Stanford University. His research interests focus on measuring uncertainty from data with minimal assumptions. This includes the method of empirical likelihood, which provides likelihood inferences without assuming parametric model forms. He has also worked on randomized quasi-Monte Carlo which attains close to an error rate n -3/2 for integration of smooth multidimensional functions while allowing sample driven error estimates.
The award-winning paper will be presented by Professor Owen at the Annual Meeting of the Statistical Society of Canada to be held in Toronto, Ontario, May 25-28.
Lise Manchester Award
Lise Manchester Award: Agnes Herzberg
Professor Agnes Herzberg is the 2014 recipient of the Lise Manchester Award. This biennial award is given by the Statistical Society of Canada in commemoration of the late Dr Lise Manchester’s abiding interest in using statistical methods to study matters of relevance to society. The award recognizes excellence in statistical research which considers problems of public interest and which is potentially useful for formation of Canadian public policy.
Agnes Herzberg obtained her PhD from the University of Saskatchewan. She spent her early career in the Department of Mathematics at the Imperial College of Science and Technology, London, and more recently in the Department of Mathematics and Statistics at Queen’s University, where she is currently a Professor Emeritus. Agnes has a long and distinguished record of research in experimental design and applied statistics. In the 1960’s and 1970’s, she was at the forefront of research on rotatable response surface designs. She also contributed extensively to the theory of optimal experimental design. In the past two decades, Agnes has made substantial contributions in methodological areas such as model selection, robust designs and experimental design for medical experiments as well as her contributions to the application of statistics in public policy.
In 1999 Agnes was awarded the SSC Distinguished Service Award in recognition of her long and excellent service to the Society and to the development of the statistical sciences in Canada as well as the International Statistical Institute’s Henri Willem Methorst Service Medal. She was president of the SSC in 1991-1992 and was elected to the Royal Society of Canada in 2008. Agnes was named an Honorary Member of the SSC in 2007. She has held offices in a number of statistical societies, and had editorial responsibilities in several top journals. As president of the SSC, she inaugurated a series of sessions on Science and Statistics, bringing to the annual meetings distinguished scientists, social-scientists and journalists.
For 19 years, starting in 1996, Agnes Herzberg has organized the annual Conference on Statistics, Science and Public Policy selecting topics ranging through science, public policy, education, risks, ethics, health, globalization and democracy for discussion among a selected group of scientists, policy makers, journalists, heads of regulatory agencies and other influential participants. She has been responsible for the editing and publication of the 19 conference proceedings to inform public policy.
Because of her vision, courage, and sheer hard work, through these conferences and their publications, she has made a most unique and significant contribution.
The citation for the prize reads:
“To Agnes Herzberg, for bringing together statisticians, scientists, politicians and public servants from Canada and around the world annually since 1996 to tackle problems at the intersection of statistics, science and public policy at the Conference on Statistics, Science and Public Policy focused on creating a network of experts to discuss current and emerging issues of topical interest and improve public policy to deal with them.”
SSC Impact Award
SSC Impact Award: John Petkau
The 2014 recipient of the Statistical Society of Canada Award for Impact of Applied and Collaborative Work is A. John Petkau, Professor in the Department of Statistics at the University of British Columbia, Vancouver. The award recognizes outstanding contributions by members of the SSC in collaborative research and applied work, the importance of which derives primarily from its relatively recent impact on a subject area outside of the statistical sciences, on an area of application, or on an organization.
John was born in 1950 in Carman, Manitoba and grew up on three different farms in the vicinity of the neighbouring town of Elm Creek, a community about 70 kilometres west of Winnipeg. As a lad, he benefited from the tutelage of his older sister, who taught him to speak English before he started school at Wingham Elementary. His later education was at Elm Creek Elementary and High Schools, where he was one of three males in his 1967 graduating class of twelve students.
John began his university education at the University of Manitoba. When he was searching for additional science courses to take in first year, a future brother-in-law suggested he enroll in a second year introductory statistics course, giving him the opportunity to become aware of a discipline he had no idea existed. During his subsequent undergraduate studies concentrating in Mathematics and Statistics and completed in 1971, he was challenged and advised by many excellent instructors, among others B. Johnston, B.K. Kale, P. McClure, N.S. Mendelsohn, K. Mount, J.N.K. Rao, and R. Wong.
John continued to a PhD program in Statistics at Stanford, graduating in 1975. Here he was inspired by the many outstanding faculty and benefitted from valuable mentoring not only by his PhD supervisor, Herman Chernoff, but also by others including Lou Gordon, Paul Switzer and Ingram Olkin. In his thesis research, he formulated the problem of designing a clinical trial as a Bayes sequential decision problem, utilized a connection to optimal stopping problems for Wiener processes and developed numerical methods for evaluating approximate solutions. These types of problems were the focus of much of his early research and his interest in sequential approaches continues to the present.
John moved to MIT to take up an instructorship in 1974, accompanying Chernoff who was to establish a statistical presence within the Department of Mathematics. Beyond the opportunity to continue to collaborate closely with Chernoff, the two years spent at MIT provided valuable experience in developing courses and initiating programs.
John’s first study leave after moving to UBC in 1976 was spent in the Harvard Department of Biostatistics in 1981-82, where he had the opportunity to advise and collaborate with clinical researchers at the Massachusetts General Hospital. The stimulation provided by this experience prompted efforts to become more involved with collaborative research at UBC. This led to contact with Professor Don Paty who had recently moved to Vancouver to head the Multiple Sclerosis (MS) clinic at the UBC Hospital. This somewhat random initial event has led to many collaborations over subsequent years, both at UBC and elsewhere, and has led to the longest thread in John’s research path and the one with the largest impact.
John’s MS collaborations have addressed issues of specific concern to the discipline, particularly issues related to improving how MS clinical trials are designed, executed and analyzed. These subject-area issues have provided many opportunities for methodological research of immediate applicability. A theme running through this work is the development of approaches that make better use of the rich longitudinal data collected on MS patients. John has made contributions via modeling longitudinal data with mixed and hidden Markov models, via improving experimental designs, and in general bringing best statistical practices to MS research. His work has helped researchers to identify factors that counteract the effects of very expensive medication, providing guidance to allow people with MS to switch from futile medications to something more effective. In recent work with UBC MS researcher Dr Helen Tremlett, John contributed to the surprising observational study that showed there was little evidence of the long-term effectiveness of the commonly used beta-interferon drugs. His work on the use of magnetic resonance imaging (MRI) outcomes as potential surrogates has been influential in phase II clinical trials. Currently he is developing a new safety monitoring approach for detecting unusual increases in the MRI lesion counts of individual patients that might indicate an increased risk of imminent clinical worsening. The respect John has in the MS community is evidenced by his many collaborations, his invitations to subject-area workshops and conferences, and his extensive service on advisory boards and monitoring committees.
Another subject-area in which John has had major collaborations is environmental epidemiology. John was among the earliest statisticians to study connections between air pollution and human health, in particular the health effects of inhalable particulate matter. The analysis of the longitudinal data was complicated by the presence of missing data and the computational challenges of many long sequences. To handle these challenges, John enlisted the department’s Statistical and Consulting Research Laboratory (SCARL) to develop suitable software to implement the then new methodology of generalized estimating equations. John’s involvement in environmental epidemiology diminished as his involvement in MS continued to expand.
John has contributed in many ways to the UBC Statistics Department, including as Head (1989-1994) and as frequent Faculty Advisor to SCARL. Perhaps most importantly, his vision of the statistical sciences is felt throughout the Department – in its faculty, in its curriculum and in the importance of SCARL.
John has also contributed to the discipline of statistics at the national level. He has served the SSC as a Regional Representative on the Board of Directors (1982-84, 2003-05), as President of the Biostatistics Section (1996-97), and as Chair of the Pierre Robillard Committee (1983-84), the Program Committee for the 1988 Annual Meeting, the Awards Committee (1990-91) and the Research Committee (1999-2002). He also served as Chair of the NSERC Statistical Sciences 1989-90 GSC and 2000-02 Reallocations Exercise Steering Committee. Currently, he is the SSC President-Elect.
No assessment of John’s impact is complete without considering his influence on young statisticians – his mentoring and the example he sets with his high standards. His impact on applied statistical methodology is far-reaching through his instilling in students the importance of analyzing data in a way that honours the data and addresses the scientific question of interest.
John is greatly indebted to his UBC colleagues for the stimulating and supportive work environment in the Department of Statistics, to his many wonderful collaborators at UBC and elsewhere, and to the many outstanding students who have been part of his academic life. He credits much of his success to his wife Barbara, a native Vancouverite, whom he met on a volleyball court in 1977. Barbara has been a constant source of exceptional support and has also succeeded in keeping John involved in a variety of non-academic activities. John enjoys travelling, attending the theatre, hiking, snowshoeing, reading and escaping to their cabin on Lummi Island, the “tranquil and forgotten” San Juan Island.
The citation for the award reads:
“To John Petkau, for contributions to the development, implementation and dissemination of statistical methodology related to the health sciences; for helping to bring a deeper understanding of the health effects of pollution and, through his work on design and analysis, an insight into the disease course of Multiple Sclerosis and the effectiveness of various treatments for this debilitating disease; for inspiring decades of statistics students to collaborate effectively with researchers to answer important subject-area questions.”