Jun Song

Department of Statistics, Korea University, 145 Anam-ro, Seongbuk-gu, Seoul, 02841, South Korea


I am an Assistant Professor in the Department of Statistics at Korea University. My research interests include dimension reduction, functional data analysis, statistical machine learning, and graphical models.

Prior to joining KU in 2021, I worked at The University of North Carolina at Charlotte as an Assistant Professor of Statistics and an Affiliated Faculty in the School of Data Science. I received a Ph.D. in Statistics at The Pennsylvania State University, B.S. in Statistics and B.S. in Mathematical Sciences at Seoul National University in South Korea.

Download my CV.

Last modified May, 2021.


Pennsylvania State University

Ph.D. in Statistics
Advisor: Professor Bing Li
August 2012 - August 2017

Seoul National University

B.S. in Statistics, Seoul National University
B.S. in Mathematical Sciences, Seoul National University
March 2004 - February 2011

Academic Position

Korea University

Assistant Professor, Department of Statistics
September 2021 - Present

University of North Carolina at Charlotte

Assistant Professor, Department of Mathematics and Statistics
Affiliated Faculty, School of Data Science (from August 2020)
August 2017 - June 2021

Grants & Awards

  • UNC Charlotte, Faculty Research Grant Award, sole PI, 2018–2019.
  • Penn State, William Harkness Teaching Award, 2016.
  • Penn State, Jack and Eleanor Pettit Scholarship in Science, 2016
  • Penn State, William Harkness Travel Award for JSM Seattle, 2015
  • Penn State, August and Ruth Homeyer Graduate Fellowship, 2012–2013
  • Penn State, University Graduate Fellowship, 2012–2013.
  • Seoul National University, Brain Korea 21 Fellowship, 2011–2012.
  • Korea Science and Engineering Foundation, National Science and Technology Scholarship, Korea, 2004–2010.

Research Interests

  • Sufficient dimension reduction
  • Functional data analysis
  • High-dimensional problem
  • Statistical analysis of complex data structure, including functional data and tensor data
  • Statistical machine learning


: Graduate student, *: Corresponding author
  • Bing Li and Jun Song (2021+)

    Dimension reduction for functional data based on weak conditional moments

    The Annals of Statistics (Accepted)
  • Paul H. Jung and Jun Song* (2021+)

    Multivariate Neighborhood Trajectory Analysis: An Exploration of the Functional Data Analysis Approach

    Geographical Analysis (Accepted)
  • Jun Song* and Bing Li (2021)

    Nonlinear and additive principal component analysis for functional data

    Journal of Multivariate Analysis, 181, 104675.
  • Jun Song* (2019)

    On sufficient dimension reduction for functional data: Inverse moments based methods

    WIREs: Computational Statistics, 11(4), e1459.
  • Holly Holt, Gabriel Villar, Weiyi Cheng, Jun Song, and Christina Grozinger (2018)

    Molecular, physiological and behavioral responses of honey bee (Apis mellifera) drones to infection with microsporidian parasites

    Journal of Invertebrate Pathology, 155, 14-24.
  • Bing Li and Jun Song (2017)

    Nonlinear sufficient dimension reduction for functional data

    The Annals of Statistics, 45, 1059--1095.


  • Ali Mahzarnia and Jun Song* (2021+)

    Multivariate functional group LASSO: functional predictor selection

  • Jun Song and Kyongwon Kim

    Sparse Multivariate Functional PCA


In preparation

  • Ali Mahzarnia and Jun Song* (2021+)

    Nonlinear and additive functional group sparse regression: nonlinear functional predictor selection

  • Bing Li and Jun Song

    Sufficient dimension reduction for general tensor product

  • Jun Song and Won Chang

    Calibration of High-dimensional Spatial Data via nonlinear sufficient dimension reduction

  • Jun Song, Naomi S. Altman, and Kalyan Das

    Self-modeling Nonlinear Poisson regression model

  • Jun Song, Bing Li, and Hannu Oja

    On functional Spearman's correlation and the related canonical correlation analysis

Instructor at

  • STAT 7133/8133: Multivariate Analysis (graduate course)
  • Spring 2018, Spring 2019.
  • STAT 6115/DSBA 6115: Statistical Learning with Big Data (graduate course)
  • Fall 2018, Fall 2019, Fall 2020, Fall 2021.
  • STAT 3122: Probability and Statistics I
  • Spring 2019.
  • STAT 2122: Introduction to Probability and Statistics
  • Spring 2020, Fall 2020, Spring 2021, Fall 2021.
  • STAT 1221/1222: Elements of Statistics I / Introduction to Statistics
  • Fall 2017, Fall 2018, Fall 2019, Spring 2020.
  • STAT 414/MATH 414: Introduction to Probability Theory
  • Summer 2016.
  • STAT 318/MATH 318: Elementary Probability
  • Fall 2015 and Spring 2016.
  • STAT 414: Introduction to Probability Theory (Online)
  • Summer 2015.

Other Experiences

Pennsylvania State University

Graduate Assistant, Department of Statistics
August 2012 - August 2017

Seoul National University

Graduate Assistant, Department of Statistics
March 2011 - June 2012

Bank of Korea

Research Assistant
October 2008 - November 2008

Boston Consulting Group

Research Assistant
August 2008 - September 2008

Republic of Korea Army

Sergeant (Mandatory Military Service)
February 2005 - February 2007