UNIVERSITY PARK, Pa. — Lingzhou Xue, professor of statistics at Penn State, will present a talk titled “Beyond the Bell Curve Assumption: Recent Advances in Statistical Graphical Models” as part of the Department of Statistics public lecture series. The lecture will be held on Thursday, April 9, at 3:30 p.m. in 201 Thomas Building at University Park with a reception to follow outside 327 Thomas.
“In our data-driven world, finding the hidden relationships between thousands of variables is a major scientific challenge,” Xue said. “From constructing gene regulatory networks to understanding functional brain connectivity, statistical graphical models have become fundamental tools for helping us visualize and understand such complex dependencies in high-dimensional data. However, traditional approaches have heavily relied on idealized assumptions of the Gaussian or 'bell curve' distribution. We will discuss the development of scalable estimation methods that relax these strict distributional assumptions without sacrificing theoretical guarantees."
In his research, Xue explores how to build reliable models and learn from large and complex datasets. Much of his recent work focuses on learning from data collected across diverse sources, and designing models that can support better decision-making in areas such as health, the environment and society.
Xue received a bachelor's degree in statistics from Peking University in 2008 and a doctoral degree in statistics from the University of Minnesota in 2012. He was a postdoctoral research associate at Princeton University from 2012 to 2013.
“The public lecture series aims to introduce the broader community to the exciting research done by faculty in the Department of Statistics at Penn State,” said Nicole Lazar, department head and professor of statistics. “I am delighted to highlight the work of Professor Lingzhou Xue — who is making important contributions in machine learning and artificial intelligence — this semester."