Profiles

Contact Information:
Richard J. Cook

My personal website
My books with Jerry Lawless
Biostatistics graduate program
 

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. I have been working on a broad spectrum of areas including recursive partitioning learning, causal inference, dependence modelling, Bayesian methods, and two-phase design.

Contact Information:
Emily Kozlowski

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:
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:
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:
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:
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.