Profiles

Contact Information:
Audrey Béliveau

Research Interests

My research develops statistical methods for real-world applications, with a recent focus on advancing network meta-analysis to synthesize the comparative effectiveness and safety of medical interventions. I also work on environmental and ecological problems, including estimating methane emissions from aerial surveys. My expertise includes Bayesian modeling, survey sampling, and capture–recapture methods.

Contact Information:
Christian Boudreau
 

Research interests

Professor Boudreau's research interests include survival analysis, event history analysis, survey sampling, and longitudinal data.

Research interests

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.

Contact Information:
Jun Cai

Jun Cai's personal website

Research interests

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.

Contact Information:
Shoja Chenouri

Research interests

Professor Chenouri's research interests include:

Contact Information:
Richard J. Cook

My personal website
My books with Jerry Lawless

Research interests

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.

Contact Information:
Cecilia Cotton

Research interests

The underlying theme of my research interests is using longitudinal data to solve problems in public health:

• Inference for comparing survival across multiple dynamic treatment regimens based on observational longitudinal data.
• Applications to epoetin dosing strategies for hemodialysis subjects with chronic kidney disease.
• Joint modeling of longitudinal and survival data in the context of causal inference.

Contact Information:
Charmaine Dean

Role & Research Interests

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.

Contact Information:
Liqun Diao

Research Interests

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.

Contact Information:
Steve Drekic

Steve Drekic's Google Scholar profile

Research interests

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.

​Contact Information:
Joel Dubin

​Health Data Science Lab (HDSL) Lead:

HDSL Website 

Research interests

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.

Contact Information:
Ben Feng

Ben's personal website
 

Research Interests

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.

Contact Information:
Ali Ghodsi

Ali Ghodsi's personal website

Research interests

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.

Contact Information:
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.

Contact Information:
Aukosh Jagannath

Research Interests

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.

Canada Research Chair, Risk Theory

Contact Information:
David Landriault

Research interests

Actuarial Science, Quantitative Risk Management, Applied Probability, Stochastic Process, Risk and Ruin Theory, Stochastic Control Problems in Insurance and Finance, Stochastic Modelling in Insurance

Contact Information:
Christiane Lemieux

Christiane Lemieux's personal website

Research interests

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.

Contact Information:
Bin Li

Personal website

Research interests

Stochastic control (dynamic optimization) problems in insurance, and finance, and economics.

Contact Information:
Mufan Li

Mufan Li's personal website.

Research

I am broadly interested in deep learning theory. Most recently, I have been thinking a lot about scaling limits of large neural networks and their training dynamics.

Contact Information:
Pengfei Li

Pengfei Li's personal website

Research interests

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.

Contact Information:
Kun Liang

Kun Liang's personal website

Research interests

• Large-scale inference

• Statistical genetics

• High-dimensional statistics

• Machine learning

Contact Information:
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.

Contact Information:
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.

Contact Information:
Peter MacDonald

Peter MacDonald's personal website

About

I am an Assistant Professor in the Department of Statistics & Actuarial Science at the University of Waterloo. I work primarily on statistical analysis and methods for multiple and dynamic networks. I also have interests in post-selection inference, and formally private and fair statistical methods for network data.

Research Interests

Inference for noisy dynamic networks

Contact Information:
Paul Marriott

Research interests

Professor Marriott's research activity is split between theoretical and applied work.

Contact Information:
Glen McGee

Glen McGee personal website

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.

Contact Information:
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.

Contact Information:
Jeffrey Negrea

Jeffrey's profile page.

Interests

• Online Learning
• Computational Statistics
• Statistical Learning Theory
• Applied Probability
• Markov Chains & Processes

Contact information:

Office: M3 2113
Department of Statistics and Actuarial Science
University of Waterloo
Mathematics 3, 200 University Avenue W
Waterloo, Ontario, N2L 3G1, Canada

Email: mnendel@uwaterloo.ca

Research interests

My research activities are primarily concerned with model uncertainty in economics, finance, and actuarial science with a focus on the valuation of financial and insurance products under model uncertainty using non-linear partial differential equations. In addition, I work on mathematical topics related to regulatory policymaking, risk measures, and mean field games.

Contact Information:
Yingli Qin

Yingli Qin's personal website

Research interests

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.

Contact Information:
Greg Rice

Research interests

Greg’s current research interests are: Functional Data Analysis, Time Series Analysis, Change Point Analysis, Panel Data, and Central Limit Theory for Stationary Processes.

Contact Information:
Peijun Sang

Peijun Sang's personal website

Research interests

• Functional data analysis
• High-dimensional regression analysis
• Copula and dependence modelling
• Streaming data and online learning problems
• PU learning and semi-supervised learning

Contact Information:
David Saunders

David Saunders's personal website

Research interests

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.

Contact Information:
Alexander Schied

Research Interests

Alexander Schied’s research focuses on quantitative finance, probability theory, and stochastic analysis, with recent work on risk measurement and management, financial modelling and optimization, robustness and model uncertainty, and market microstructure. He is co-author, with Hans Föllmer, of the book Stochastic Finance: An Introduction in Discrete Time. 

Contact Information:
Matthias Schonlau

Matthias Schonlau's personal website

Research interests

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.

Contact Information:
Yi Shen

Personal Website

Research Interests

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.

Contact Information:
Stefan Steiner

Research interests

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.

Contact Information:
Nathaniel Stevens

Nathaniel is interested in using data to make decisions, solve problems, and improve processes. His research program lies at the intersection of data science and industrial statistics, making 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. Nathaniel has also 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. 

Contact Information:
Alex Stringer

Alex Stringer's personal website

About

I am an assistant professor in the Department of Statistics and Actuarial Science at the University of Waterloo in Canada. My research is on computational statistics and semi-parametric regression modelling. I have worked on methods and theory for approximate integration in statistical problems, methods for benchmark dose analysis in environmental toxicology, methods for fast Bayesian inference (without MCMC) including in spatial models, and some methods and theory for additive and random effects models.

Contact Information:
Qinglong Tian

Qinglong Tian's personal website

Research

My current research focuses on transfer learning, particularly addressing challenges related to distributional shift, out-of-distribution detection, and label noise. I approach these problems through the lens of mixture models and density ratios, which are fundamental concepts in statistics.

Contact information:

Michael Wallace

Michael Wallace's Personal Website

Research interests

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.

Contact Information:
Office: M3 3122
Phone: 519-888-4567, ext. 31569
Email: wang@uwaterloo.ca

Ruodu Wang's personal website

Research interests

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.

Contact Information:
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.

Contact Information:
Chengguo Weng

Chengguo Weng's personal website

Research interests

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.

Contact Information:

Tony Wirjanto

Tony Wirjanto's personal website

Research interests

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.

Contact information:

Samuel Wong

Samuel Wong personal website

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.

Contact Information:
Changbao Wu

Changbao Wu's personal website

Research interests

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.

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.

Contact Information:
Fan Yang

Research interests

Fan Yang’s research interests lie in the areas of quantitative risk management, actuarial science and mathematical finance.

Contact Information:
Leilei Zeng

Research interests

Professor Zeng's research interest lies in the development of statistical methodologies for public health and medical research.

Contact Information:

Kenneth Zhou

Kenneth Zhou’s personal website

Research interests:

Kenneth's research interests lie at the intersection of actuarial science, statistics, and finance, with a focus on human mortality and longevity risk. The overarching goal is to develop theoretical frameworks and practical tools for modeling how people age and die, with consideration of individual heterogeneity, demographic fairness, and actuarial equity in insurance and pension design.

Contact Information:
Mu Zhu

Mu Zhu personal website

Research interests

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.

Contact Information:
Yeying Zhu

Yeying Zhu's personal website

Research interests

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.