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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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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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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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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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Audrey Béliveau
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.
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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.
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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.
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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.
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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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Alexander Schied
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.