Bovas Abraham
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Bovas Abraham
Research interests
Research interests are in time series analysis and statistical methods for quality improvement.
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Bovas Abraham
Research interests are in time series analysis and statistical methods for quality improvement.
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Ilham Akhundov
Mathematics, Business and Accounting programs
Asymptotic methods in probability theory and mathematical statistics.
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Doug Andrews
After a successful career as an actuary and a Chartered Financial Analyst (CFA), I am contributing to the actuarial profession through research, university teaching and advising those interested in joining the profession. My research has an international perspective and is designed to produce practical policy recommendations. It is focused on investments, risk management, financial economics, aging, and their implications for the management of social support systems, such as pensions, health care, and long-term care.
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Peter Balka
Peter has been program director for the Math/CA program since 2006. Prior to his appointment as faculty lecturer in the Department of Statistics and Actuarial Science at the University of Waterloo in 2003, Peter was a faculty member at the University of Alberta and at the College of the Rockies. Peter has a BSc and MSc (biostatistics) from the University of Guelph.
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Surya Banerjee
Statistics, game theory, development economics, and economic theory.
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Audrey Béliveau
My research is mainly concerned with Bayesian hierarchical modeling and is motivated by applications in a variety of fields, namely ecology and epidemiology. A lot of the problems I work on involve the integration of multiple sources of data in a single analysis (e.g. network meta-analysis in epidemiology and integrated population modeling in ecology). I have a number of interdisciplinary collaborations with academics as well as industry partners.
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Peter Blake
Peter Blake has a Bachelor of Mathematics degree (Chartered Accountancy - Co-op) from the University of Waterloo and is a Chartered Professional Accountant.
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Christian Boudreau
Professor Boudreau's research interests include survival analysis, event history analysis, survey sampling, and longitudinal data.
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Robert Brown
Rob’s research focus is the design of financial security programs in times of rapidly shifting demographics. In his 39 years at Waterloo, Rob wrote seven books and over 50 refereed papers.
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Steve Brown
Professor Brown is a biostatistician whose research interests include the development of statistical methods for the design of community-based interventions, the analysis of longitudinal data collected from studies of interventions designed to affect health behaviours, and the design and analysis of observational studies of health behaviour.
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Ryan Browne
Ryan’s current research focus is model-based clustering and classification. In addition he is interested in measurement models, specifically in assessing the quality of a measurement system. This work was the focus of his PhD thesis.
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Jun Cai
Professor Jun Cai's research interests are in the fields of actuarial science, applied probability, and mathematical finance, with focuses currently on quantitative risk management for insurance and finance, insurance decision problems, dependence modelling, and risk analysis with model uncertainty.
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Shoja Chenouri
Professor Chenouri's research interests include:
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Richard J. Cook
My personal website
My books with Jerry Lawless
Biostatistics graduate program
My research interests include the development and application of statistical methods for public health. Specific areas of interest include the analysis of life history data, longitudinal data, incomplete data, sequential methods, multivariate analysis, clinical trial design, and the assessment of diagnostic tests.
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Cecilia Cotton
The underlying theme of my research interests is using longitudinal data to solve problems in public health:
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Dina Dawoud
Statistics education.
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Charmaine Dean
Charmaine Dean is Vice-President, Research and Professor in the Department of Statistics and Actuarial Science at the University of Waterloo. Her research interest lies in the development of methodology for disease mapping, longitudinal studies, the design of clinical trials, and spatio-temporal analyses. Much of this work has been motivated by direct applications to important practical problems in biostatistics and ecology. Her current main research applications are in survival after coronary artery bypass surgery, mapping disease and mortality rates, forest ecology, fire management, smoke exposure estimation from satellite imagery, and modeling of temporary and intermittent stream flow for flood analysis and predictions.
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Liqun Diao
I am interested in developing and applying data-driven statistical methods and machine learning algorithms to advance knowledge in fields including medicine, public health, and insurance. I have been working on a broad spectrum of areas including recursive partitioning learning, causal inference, dependence modelling, Bayesian methods, and two-phase design.
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Steve Drekic
Steve Drekic's Google Scholar profile
Professor Drekic has co-authored over 40 articles, and has published in key journals across several disciplines, including actuarial science, operations research, and statistics. His work has garnered particular attention in the fields of applied probability, insurance risk/ruin theory, and queueing theory. Professor Drekic's expertise lies in the use of probabilistic/stochastic techniques with advanced computational methods to analyze mathematical problems arising in several different application areas.
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Joel Dubin
Health Data Science Lab (HDSL) Lead:
My primary research interest is in the area of methodological development in longitudinal data analysis, including for multivariate longitudinal data, where more than one outcome, (e.g., systolic and diastolic blood pressure) are each followed for individuals over time. Methods pursued for this type of data include the correlation of different longitudinal outcomes over time using curve-based methods, and incorporating lags and derivatives of the curves. I am also interested in change point and latent response models for longitudinal data, as well as prediction models, including the consideration of similarity to improve prediction accuracy.
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Ben Feng
Professor Feng’s research interests include quantitative risk management, financial engineering, Monte Carlo simulation design and analysis, and nonlinear optimization.
Professor Feng is particularly interested in the intersection of these fields such as statistical machine learning, portfolio optimization, efficient simulation algorithms for risk management, etc. My professional background in actuarial science guides my research towards applying advanced theoretical methodologies to solve complex practical problems.
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Keith Freeland
Keith Freeland obtained his Bachelor of Science degree in Actuarial Science from the University of Calgary and his PhD in Business Administration from the University of British Columbia. In 1991, he received his American Statistical Association (ASA) designation from the Society of Actuaries.
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Ali Ghodsi
Machine learning, Deep learning, Computational statistics, Dimensionality reduction, Natural language processing, Bioinformatics.
Professor Ghodsi's current research sweeps across a broad swath of AI encompassing machine learning, deep learning, and dimensionality reduction. He studies theoretical frameworks and develops new machine-learning algorithms for analyzing large-scale data sets, with applications in natural language processing, bioinformatics, and computer vision. Dr. Ghodsi's work has been published extensively in high-quality proceedings and journals. He is the co-author of the "Elements of Dimensionality Reduction and Manifold Learning" (Springer) and several US patents. His popular lectures on YouTube have more than one million views. View a complete list of his online lectures.
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Mario Ghossoub
My research is mainly concerned with model uncertainty and the modern theory of choice under uncertainty and ambiguity, and with their use and applications in insurance, risk measurement and management, quantitative behavioral finance, and the theory of risk sharing.
More information on my personal webpage.
Distinguished Professor Emeritus 1926-2016
My research focuses on risk management strategies for long term contingent risks. The work is problem-driven, using theory and methodology from financial engineering, statistics and actuarial science. Much of my current research seeks to measure and promote fairness, efficiency and transparency in the design and implementation of insurance and pension risk solutions.
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Jeanette O'Hara Hines
Jeanette O'Hara Hines' research has focused on the practical needs of researchers in the biological sciences, who frequently pose challenges with new ways of gathering data, or with new objectives. Jeanette's ongoing research project is the analysis of clustered or longitudinal data with categorical responses, a type of data frequently gathered in the biological and medical areas.
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Aukosh Jagannath
I am a mathematician working at the interface of mathematical physics, mathematical data science, optimization, and high-dimensional statistics. There are deep connections and analogies arising at the interface of these four fields. The common threads tying them together are fundamental problems in mathematics. The goal of my research is to understand the statistical properties of high-dimensional, complex energy landscapes and how these properties affect the behaviour of algorithms and dynamical systems on these landscapes. I first began studying these questions from the perspective of statistical physics, with an emphasis on analyzing glassy systems. More recently, I have turned to analyzing the average case behaviour of optimization and sampling problems arising in combinatorics, data science, and high-dimensional statistics.
Olga Kanj completed her Ph.D. in Finance at Lazaridis School of Business and Economics in 2020. Kanj also holds an MBA in Finance and Economics and BBA in Banking and Finance from Notre Dame University-Louaize with highest distinction.
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Adam Kolkiewicz
Professor Kolkiewicz's research interests are primarily in the areas of statistics and financial mathematics. In statistics, he has focused on statistical tools for time series analysis, robust methods of estimation, and asymptotic methods of inference.
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Emily Kozlowski
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David Landriault
Actuarial Science, Quantitative Risk Management, Applied Probability, Stochastic Process, Risk and Ruin Theory, Stochastic Control Problems in Insurance and Finance, Stochastic Modelling in Insurance
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Jerry Lawless
My research interests cut across several areas of statistics, including survival and event history analysis, modeling, theory and methods for estimation and prediction, and the analysis of incomplete data. I am motivated by scientific and technical issues that arise in medicine, public health, system reliability, the social sciences and other areas.
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Christiane Lemieux
Christiane Lemieux's personal website
Professor Lemieux is interested in quasi-Monte Carlo methods and their applications. These methods can be thought of as deterministic versions of the well-known and highly used Monte Carlo method. They are designed to improve upon the performance of Monte Carlo by replacing random sampling by a more uniform sampling mechanism based on low-discrepancy point sets. A major goal of Professor Lemieux's research is to improve the applicability of quasi-Monte Carlo methods to a wide variety of practical problems.
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Bin Li
Stochastic control (dynamic optimization) problems in insurance, and finance, and economics.
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Pengfei Li
Professor Li's research interests concern some areas of statistics, including finite mixture model, asymptotic theory, empirical likelihood, inference with constraints, experimental design, and smoothing technique.
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Fangda Liu
Research Interests
Dr. Liu’s research interests lie in actuarial science and quantitative risk management. Her recent research focuses on the study of model uncertainty in (re-)insurance design problems and risk aggregation problems.
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Kun Liang
Large-scale inference
Statistical genetics
High-dimensional statistics
Machine learning
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Martin Lysy
Research interests
I enjoy working on a variety of applied problems, for which statistical and computational methodologies fall under the three following themes.
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Jock MacKay
My research interests span a variety of areas in the application of statistical methods to the improvement of manufacturing processes, including experimental design and observational methods. In collaboration with my colleague Stefan Steiner, we have developed these methods into a system for reducing variation in process outputs. This work led to our book, Statistical Engineering.
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Paul Marriott
Professor Marriott's research activity is split between theoretical and applied work.
Brent Matheson began his career in biology and holds a Bachelor of Science and a Masters of Science in microbiology. As his interests shifted towards the business world he went back to university to complete a Masters of Business Administration (MBA) and subsequently a Chartered Financial Analyst (CFA) charter. He holds a Derivatives Market Specialist (DMS) designation through the Canadian Securities Institute.
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David Matthews
Professor Matthews' research interests encompass the fields of biostatistics, quality improvement-especially in relation to health care-and statistical consulting. He is particularly concerned with finding effective ways to communicate statistical ideas and results to clinical researchers.
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Glen McGee
Research interests
My research interests mainly lie in developing statistical tools to solve problems in epidemiology, environmental health, and health policy. I’m currently interested in Bayesian frameworks for modelling multi-pollutant mixtures, designing and analyzing multigenerational studies, and more broadly in methods for longitudinal and cluster-correlated data.
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Don McLeish
Professor McLeish's research interests cover a variety of areas including probability and stochastic processes, statistical inference using estimating functions, and applications of Monte Carlo methods to finance.
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Riley Metzger
Statistics education.
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Zelalem Negeri
I am an Assistant Professor in the Department of Statistics and Actuarial Science. I completed a two-year Post-Doctoral Fellowship at McGill University before joining the University of Waterloo on July 1, 2022.
My research interest focuses on developing and validating statistical methods for applications in public health research, emphasizing both aggregate data and individual participant data meta-analyses of diagnostic and screening test accuracy studies. My research uses computational statistics methods such as parametric and non-parametric bootstrap approaches and deterministic and Monte Carlo expectation-maximization (MCEM) algorithms.
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Wayne Oldford
Wayne Oldford's personal website
Statistical reasoning, exploratory data analysis, data visualization, and the development of interactive computational environments that support these activities, comprise the broad areas of Professor Oldford's research interests.
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Yingli Qin
Professor Qin's current research effort is mainly devoted to hypothesis testing for high-dimensional data with applications to gene sets testing and estimating and testing for large dimensional covariance matrices using the random matrix theory.
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Greg Rice
Greg’s current research interests are: Functional Data Analysis, Time Series Analysis, Change Point Analysis, Panel Data, and Central Limit Theory for Stationary Processes.
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David Saunders
David Saunders's personal website
Decision making under uncertainty is prevalent in all human endeavours. The pervasive need to make critical decisions while faced with imperfect knowledge of the future is perhaps most acute in the area of finance. This has resulted in a commensurate demand for tools that allow market participants to analyze and manage their risks effectively. Professor Saunders' research focuses on the application of stochastic optimization and probability, particularly to problems in finance.
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Alexander Schied
Alexander Schied’s research is in probability theory and stochastic analysis with applications to mathematical finance and economics. Recent research topics include risk measurement and risk management, modeling and optimization in finance and economics, robustness and model uncertainty, and issues arising from market microstructure and price impact. Together with Hans Föllmer he co-authored the book Stochastic Finance: An Introduction in Discrete Time. He holds a doctoral degree in mathematics from the University of Bonn.
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Matthias Schonlau
Matthias Schonlau's personal website
Professor Schonlau's research interests include applied survey sampling and survey methodology, statistical machine learning from text data such as open-ended questions as well as software implementation.
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Yi Shen
My main research area is applied probability. Currently I focus on understanding the relation between the random locations (e.g., the location of the path supremum, the hitting times, etc.) and the probabilistic symmetries of stochastic processes/random fields, such as stationarity, self-similarity, exchangeability, etc. I am also working on characterizing these symmetries using various tools including extreme value theory and ergodic theory.
More generally, I am enthusiastic about various problems in probability, such as random algebraic topology, limit theorems and financial mathematics. I am also interested in the applications of probability in statistics, physics, econometrics and actuarial science.
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Diana Skrzydlo
Diana Skrzydlo’s personal website
Diana Skrzydlo is a Continuing Lecturer in the Department of Statistics and Actuarial Science, the Math Faculty Teaching Fellow, and the current Director of the MActSc program. She has been teaching at the University of Waterloo since 2007 and has spoken widely on innovative teaching and assessment techniques, including in Indonesia with the READI project. In 2017-18 she developed a faculty mentorship program for the department, and started a monthly teaching discussion group. She won the SAS department teaching award in 2016 and the Faculty of Math Distinction in Teaching Award in 2019. She has a BMath (2006) and MMath (2007) from UW, and achieved her ASA designation from the Society of Actuaries in 2018, where she volunteers as a member of the Education & Research Section council, an LTAM grader, and on the FAP committee.
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Christopher Small
Christopher Small's personal website
Professor Small's research interests are in statistical inference, including estimating functions; and some areas of statistical geometry, including the statistical analysis of shape. Recently, he has been working on a book on asymptotic techniques.
David Arthur Sprott, one of the pioneers and leaders of statistics in Canada, died on December 13, 2013 in Waterloo, ON. He was 83.
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Stefan Steiner
Watfactory virtual manufacturing process information (PDF)
Watfactory virtual manufacturing process login
Professor Steiner's research interests cover the broad area of business and industrial statistics focusing on process improvement. The overall goal of his research is the development of innovative ways to use process data and statistical methods to drive process improvement and variation reduction.
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Nathaniel Stevens
In general Nathaniel is interested in using data to make decisions, solve problems, and improve processes. Specifically, his research interests lie at the intersection of data science and industrial statistics. He is interested in methodological developments in experimental design and A/B testing, process monitoring and network surveillance, reliability and survival analysis, and the assessment and comparison of measurement systems. Recently Nathaniel has developed a family of comparative probability metrics that may be used in place of traditional hypothesis tests in any setting that requires a comparison of statistical quantities.
Math Faculty Teaching Fellow
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Cyntha Struthers
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Mary Thompson
Professor Thompson works primarily in survey methodology and sampling theory. Her book Theory of Sample Surveys describes the mathematical and foundational theory in detail; it also contains a systematic approach to using estimating functions in surveys, and a thorough discussion (with examples) of the role of the sampling design when survey data are used for analytic purposes.
Estimation for stochastic processes has been another theme of her research. These twothemes come together in aspects of inference from complex longitudinal surveys. Issues in the design of longitudinal surveys to support causal inference are central to work on the International Tobacco Control Survey, with which Professor Thompson has been involved since 2002. She studies the application of multilevel models and longitudinal models with time-varying covariates to complex survey data, including the best ways to adapt the estimating functions systems for use with survey weights, and the use of resampling techniques to provide accurate interval estimates.
She is also currently collaborating on projects in survival and multistate models and the design of behavioural interventions on random networks.
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Michael Wallace's Personal Website
My primary research interest is in causal inference, with a specific focus on dynamic treatment regimes and personalized medicine. Dynamic treatment regimes are sequences of decision rules that take subject-level data (such as age, health status, or prior treatment) as input and recommend actions (such as which drug to take) as output. Working with longitudinal datasets, my work focuses on deriving methodologies that help identify the sequence of treatment decisions that yields the best expected outcome.
More generally, I am interested in identifying new ways to apply methods from different disciplines in new settings. This includes modifying methodology from one area of statistics so that it may be applied in a different area, or through applying statistical methods to novel problems in the 'real world' of data analysis.
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Office: M3 3122
Phone: 519-888-4567, ext. 31569
Email: wang@uwaterloo.ca
Professor Wang's research interests mainly lie in quantitative risk management, which includes various topics in actuarial science, financial engineering, operations research, probability, statistics, and economic theory.
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Lan Wen
My primary areas of research to date have been on the development and application of statistical methods in causal inference and the analysis of observational studies where complications can arise due to model misspecification, time-varying confounding and censoring/missing data. I believe that the development of novel methodologies should be rooted in practical applications. Thus, motivated by real-life applications in public health and medicine, my research addresses methodological and conceptual challenges that scientists may face in answering clinically relevant questions using real-world data studies. Challenges that arise in these observational studies include lack of randomization to the strategies of interest, and/or subjects dropping out of the study due to unknown reasons.
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Chengguo Weng
Chengguo Weng's personal website
Professor Weng’s research interests span a broad spectrum of scientific disciplines from actuarial science, finance to probability, statistics and stochastic optimization. The primary objective of Professor Weng’s research is to develop innovative risk assessment methods and prioritization strategies for actuarial and financial risk management.
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Gord Willmot
Professor Willmot's research interests involve the analysis of insurance losses, with particular emphasis on the theory and application of aggregate claims models and models for the insurer's surplus associated with a particular block of insurance business. His main approaches to the study of these models involves a variety of analytical tools, including those from applied probability and mathematical reliability theory.
Tony Wirjanto's personal website
Professor Wirjanto's research interests lie in the intersection between statistics and econometrics. In particular he conducts research in the field of financial time series with a focus on volatility modeling/forecasting and financial risk management, and in the field of financial mathematics with a focus on portfolio optimization in a high-dimensional setting and on global climate change risks.
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Research interests
My research focus is in developing methodology for data science problems, with an emphasis on applications in structural biology, dynamic systems, and engineering. I am particularly interested in using Bayesian modelling, Monte Carlo methods, and statistical computation to advance our scientific knowledge in these areas. More generally, I enjoy working on collaborative projects where principled statistical thinking can be combined with scientific expertise to solve new problems.
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Changbao Wu
Changbao Wu's personal website
Professor Wu has a primary research interest in the design and analysis of complex surveys. His research also covers more broad topics including semiparametric and nonparametric methods, resampling (jackknife and bootstrap) techniques, missing data and measurement error problems. He has worked extensively on empirical likelihood (EL) methods and related computational procedures, with strong interest in developing R packages for practical implementations of the EL methods.
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Fan Yang
Fan Yang’s research interests lie in the areas of quantitative risk management, actuarial science and mathematical finance.
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Leilei Zeng
Professor Zeng's research interest lies in the development of statistical methodologies for public health and medical research.
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Mu Zhu
Mu's initial research interest was dimension reduction. In the early years of his faculty career, he devoted much attention to efficient kernel machines for rare target detection and ensemble methods for variable selection. He also worked on algorithms for making personalized recommendations, and applications of machine learning to healthcare informatics.
While ensemble learning continued to captivate his curiosity, in more recent years Mu explored a hodgepodge of different topics—such as evaluation metrics, protein structures, transactional networks, and genetic epistasis. At present, he is studying various problems about dependence modeling, large covariance matrices, and generative neural networks.
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Yeying Zhu
Dr. Zhu’s research interest lies in causal inference, machine learning and the interface between the two. She highly appreciates the interdisciplinary nature of causal inference and aim to develop theoretically sound methods for data-driven problems.
Her recent focus is on the development of variable selection/dimension reduction procedures to adjust for confounding in observational studies in a high-dimensional setting. In addition, she has developed innovative machine learning algorithms for the modeling of propensity scores for binary, multi-level and continuous treatments.
Yangjianchen Xu Personal Website
Research Interests
My research focuses on developing novel statistical methods and theory for survival analysis to address challenges in biomedical and public health sciences. I specialize in semiparametric models for univariate and multivariate time-to-event data under right or interval censoring.