Dr. Lingzhou Xue

Professor

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Biography

Lingzhou Xue is a Professor of Statistics at Penn State University. He received his Bachelor of Science in Statistics from Peking University in 2008 and his Ph.D. in Statistics from the University of Minnesota in 2012. He worked as a postdoctoral research associate at Princeton University from 2012 to 2013. His research interests encompass high-dimensional statistics, nonparametric statistics, statistical machine learning, and large-scale optimization, focusing on applications in biomedical, environmental, and social sciences. His recent work explores topics like causal inference, federated learning, graphical models, and optimal transport. Xue has mentored numerous Ph.D. students and postdoctoral researchers, with five of his advisees securing tenure-track faculty positions. He is an elected Fellow of the Institute of Mathematical Statistics and the American Statistical Association, and an Elected Member of the International Statistical Institute. Among his accolades, he received the Emerging Leader Award from the Committee of Presidents of Statistical Societies in 2021 and the Bernoulli Society New Researcher Award in 2019. Xue serves as an Associate Editor for several prestigious journals in the fields of statistics and machine learning.

Research Interests

Experience

Postdoctoral Research Associate

— Present

Princeton University • Princeton, NJ

Awards

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Elected Fellow

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Elected Fellow

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Elected Member

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Emerging Leader Award

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New Researcher Award

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Paper Award

Requirements for Pennsylvania State University

Doctorate Program
Requirements
GPA Requirement
Required:3
TOEFL
Writing
Required:24
Speaking
Required:23
Total
Required:100
IELTS
Writing
Required:7
Speaking
Required:7
Overall
Required:7
GRE General
Prerequisites
Master's degree in related field for PhD Baccalaureate degree from accredited institution
Application Checklist
  • Three letters of recommendation
  • Statement of Purpose
  • Writing Sample
  • Official Transcripts
  • Resume/CV
Specialization Notes

GRE scores are highly recommended but not strictly required for Applied Linguistics.