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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 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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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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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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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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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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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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Kun Liang
Large-scale inference
Statistical genetics
High-dimensional statistics
Machine learning
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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.