Theory & Methods

Our faculty members are advancing the boundaries of theoretical and methodological research. They contribute to various fields, including mathematical finance, genetic epidemiology, data visualization, and beyond, employing rigorous methods to tackle complex challenges across multiple disciplines. Their work enhances the robustness of statistical models and drives interdisciplinary solutions, underpinning significant innovations in science and industry. Discover their cutting-edge research and contributions by exploring the profiles listed below.

 

Faculty

Bálint Virág
Professor Virag's research explores the interplay between probability theory and random matrices, with applications ranging from statistical physics to complex data analysis.

Chris Maddison
Assistant Professor Maddison specializes in deep learning and probabilistic modelling and has contributed significantly to advancing machine learning techniques.

Daniel Roy
Associate Professor Roy's research delves into statistical inference and learning foundations, particularly in understanding prediction, inference, and decision-making under uncertainty.

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.

Jeffrey Rosenthal
Professor Rosenthal's work includes probability theory, Markov chains, stochastic processes, and the effectiveness of Markov chain Monte Carlo (MCMC) methods.

 

Leonard Wong
Assistant Professor Wong studies algebraic aspects of differential equations with applications to mathematical physics and dynamic systems.

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.

Murat Erdogdu
Assistant Professor Erdogdu specializes in machine learning and optimization, mainly focusing on algorithmic efficiency and statistical inference in large-scale data settings.

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.

Piotr Zwiernik
Associate Professor Zwiernik works on algebraic statistics, focusing on graphical models and their applications in understanding complexity and structure in multivariate data.

Qiang Sun
Associate Professor Sun's research primarily addresses computational challenges in statistical inference, focusing on nonparametric and semiparametric methodologies.

Linbo Wang
Assistant Professor Wang develops statistical methods for complex and structured data, particularly in environmental and biological sciences.

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.

Sebastian Jaimungal
Professor Jaimungal focuses on mathematical finance, particularly stochastic control and machine learning applications in trading and risk management.

Silvana Pesenti
Assistant Professor Pesenti investigates quantitative risk management, focusing on uncertainty quantification and robust statistical methods in actuarial sciences.

Stanislav Volgushev
Associate Professor Volgushev works on robust statistical methods, dependency modelling, and their implications in econometrics and environmental statistics.

Wenlong Mou
Assistant Professor Mou's research intersects statistical theory, machine learning, and dynamic programming and aims to develop optimal decision-making tools.

Xiaofei Shi
Assistant Professor Shi specializes in statistical learning, particularly methods for large-scale data structures, with implications for network analysis and bioinformatics.

Xin Bing
Assistant Professor Bing's work focuses on high-dimensional statistics, addressing challenges in data complexity through innovative methodological developments.

Zhou Zhou
Professor Zhou's research encompasses statistical theory and methods in time series analysis, focusing on applications in economics and finance.