![](https://www.statistics.utoronto.ca/sites/www.statistics.utoronto.ca/files/Chris%20M.jpg)
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Chris Maddison
Assistant Professor Maddison specializes in deep learning and probabilistic modelling and has contributed significantly to advancing machine learning techniques.
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![Christopher Blier-Wong](https://www.statistics.utoronto.ca/sites/www.statistics.utoronto.ca/files/Christopher%20Blier-Wong.png) |
Christopher Blier-Wong
Assistant Professor Christopher's research interests lie in the intersection of actuarial science, machine learning, and statistics, with a particular focus on dependence modelling and e-variables.
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![](https://www.statistics.utoronto.ca/sites/www.statistics.utoronto.ca/files/Dan%20R.jpg)
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Daniel Roy
Professor Roy's research delves into statistical inference and learning foundations, particularly in understanding prediction, inference, and decision-making under uncertainty.
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![](https://www.statistics.utoronto.ca/sites/www.statistics.utoronto.ca/files/Dehan%20K.jpg)
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Dehan Kong
Associate Professor Kong is interested in developing novel statistical methodologies for high-dimensional data analysis, which could have applications in genetics and health sciences.
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![](https://www.statistics.utoronto.ca/sites/www.statistics.utoronto.ca/files/Jeffrey%20R.jpg)
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Jeffrey Rosenthal
Professor Rosenthal's work includes probability theory, Markov chains, stochastic processes, and the effectiveness of Markov chain Monte Carlo (MCMC) methods.
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![](https://www.statistics.utoronto.ca/sites/www.statistics.utoronto.ca/files/Jesse%20G.jpg) |
Jessica Gronsbell
Assistant Professor Gronsbell uses statistical models to improve health outcomes by better understanding electronic health records and mobile health data.
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![](https://www.statistics.utoronto.ca/sites/www.statistics.utoronto.ca/files/Leonard.jpg)
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Leonard Wong
Assistant Professor Wong studies algebraic aspects of differential equations with applications to mathematical physics and dynamic systems.
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![](https://www.statistics.utoronto.ca/sites/www.statistics.utoronto.ca/files/Mike%20E.jpg)
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Michael Evans
Professor Evans is renowned for his contributions to statistical reasoning. He focuses on evidence and model checking to improve decision-making under uncertainty.
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![](https://www.statistics.utoronto.ca/sites/www.statistics.utoronto.ca/files/Murat%20E.jpg)
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Murat Erdogdu
Assistant Professor Erdogdu specializes in machine learning and optimization, mainly focusing on algorithmic efficiency and statistical inference in large-scale data settings.
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![](https://www.statistics.utoronto.ca/sites/www.statistics.utoronto.ca/files/Nancy%20R.jpg)
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Nancy Reid
University Professor Reid is a prominent figure in theoretical statistics, specifically in likelihood inference and the role of statistical methods in scientific research.
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![](https://www.statistics.utoronto.ca/sites/www.statistics.utoronto.ca/files/Piotr%20Z.jpg)
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Piotr Zwiernik
Associate Professor Zwiernik works on algebraic statistics, focusing on graphical models and their applications in understanding complexity and structure in multivariate data.
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![](https://www.statistics.utoronto.ca/sites/www.statistics.utoronto.ca/files/Qiang%20S.jpg)
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Qiang Sun
Associate Professor Sun's research primarily addresses computational challenges in statistical inference, focusing on nonparametric and semiparametric methodologies.
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![](https://www.statistics.utoronto.ca/sites/www.statistics.utoronto.ca/files/Linbo%20W.jpg)
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Linbo Wang
Assistant Professor Wang develops statistical methods for complex and structured data, particularly in environmental and biological sciences.
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![](https://www.statistics.utoronto.ca/sites/www.statistics.utoronto.ca/files/Radu%20C.jpg)
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Radu Craiu
Professor Craiu's research includes Bayesian methods, model selection, and the development of computational techniques for complex models with applications in genetics and finance.
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![](https://www.statistics.utoronto.ca/sites/www.statistics.utoronto.ca/files/Sebastian_J.jpg)
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Sebastian Jaimungal
Professor Jaimungal focuses on mathematical finance, particularly stochastic control and machine learning applications in trading and risk management.
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![](https://www.statistics.utoronto.ca/sites/www.statistics.utoronto.ca/files/Silvana%20P.jpg)
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Silvana Pesenti
Assistant Professor Pesenti investigates quantitative risk management, focusing on uncertainty quantification and robust statistical methods in actuarial sciences.
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![](https://www.statistics.utoronto.ca/sites/www.statistics.utoronto.ca/files/Stanislav%20.jpg)
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Stanislav Volgushev
Associate Professor Volgushev works on robust statistical methods, dependency modelling, and their implications in econometrics and environmental statistics.
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![](https://www.statistics.utoronto.ca/sites/www.statistics.utoronto.ca/files/Wenlong%20M.jpg)
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Wenlong Mou
Assistant Professor Mou's research intersects statistical theory, machine learning, and dynamic programming and aims to develop optimal decision-making tools.
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![](https://www.statistics.utoronto.ca/sites/www.statistics.utoronto.ca/files/Xiaofei%20S.jpg)
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Xiaofei Shi
Assistant Professor Shi specializes in statistical learning, particularly methods for large-scale data structures, with implications for network analysis and bioinformatics.
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![](https://www.statistics.utoronto.ca/sites/www.statistics.utoronto.ca/files/Xin%20B.jpg)
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Xin Bing
Assistant Professor Bing's work focuses on high-dimensional statistics, addressing challenges in data complexity through innovative methodological developments.
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![](https://www.statistics.utoronto.ca/sites/www.statistics.utoronto.ca/files/Zhou%20Z.jpg)
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Zhou Zhou
Professor Zhou's research encompasses statistical theory and methods in time series analysis, focusing on applications in economics and finance.
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