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Feng Liang is a Professor in the Department of Statistics at the University of Illinois at Urbana-Champaign. His research focuses primarily on Bayesian statistics, statistical learning, and information theory. With a strong background in statistical methodologies and applications, he has contributed significantly to the advancement of these fields through both teaching and research. Liang's work includes developing new statistical models and methods that leverage Bayesian approaches to address complex data analysis problems. His commitment to education and mentoring has helped foster the next generation of statisticians and data scientists at one of the leading institutions in statistical learning and theory. He is actively involved in various research projects and collaborations that extend the applications of statistical principles across different domains.
GRE is optional for admission to all graduate programs in Statistics. Full status admission requires higher language scores than limited status.