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.

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:
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.

My research interests are in predictive and dependence modelling for problems in non-life insurance analytics. Correlated observations are ubiquitous in insurance loss data and characterizing their dependence is critical to the core insurance function of risk pooling. My current application focus is spatio-temporal modelling of insurance claims associated with weather property damage. As technological advances increase the availability and granularity of data, my research highlights the potential for analytics to support key operational areas in non-life insurance, including ratemaking, loss reserving, and claims management.

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:
Kun Liang

Kun Liang's personal website

Research interests

• Large-scale inference

• Statistical genetics

• High-dimensional statistics

• Machine learning

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:
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:
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:
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:
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:

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:

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.