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Kun Liang is an Associate Professor in the Department of Statistics and Actuarial Science at the University of Waterloo. He holds a PhD from Iowa State University and focuses on large-scale inference, statistical genetics, and high-dimensional statistics. His research also encompasses various aspects of machine learning, enhancing discovery rates in statistical models, and improving methodologies for data analysis in biology. Notable works include publications on false discovery rate control and adaptive filtering techniques for detecting differentially expressed genes. Liang has significantly contributed to advancements in bioinformatics and statistical methodologies, evidenced by his extensive publication record in reputable journals.
Includes fields like Clinical, Cognitive, Developmental, and Industrial/Organizational Psychology.