Kevin Moon

Mathematics and Statistics

Associate Professor


Kevin Moon

Contact Information

Office Location: Animal Science (ANSC) 214
Phone: (435) 797-0749
Email: Kevin.Moon@usu.edu
Additional Information:

Educational Background

MS, Mathematics, University of Michigan, 2016
PhD, Electrical Engineering: Systems, (Signal Processing), University of Michigan, 2016
Nonparametric estimation of distributional functionals and applications
MS, Electrical Engineering, Brigham Young University, 2012
BS, Electrical Engineering, Brigham Young University, 2011

Biography

Dr. Moon earned a bachelor's and master's degree in Electrical Engineering at Brigham Young University, focusing on signal processing. He then obtained an M.S. degree in Mathematics and a Ph.D. in Electrical Engineering at the University of Michigan where his research focused on nonparametric estimation of distributional functionals. Prior to joining Utah State University in 2018, he was a postdoctoral scholar in the Genetics Department and the Applied Math Program at Yale University where he developed methods for exploratory data analysis with a focus in biomedical applications.

Teaching Interests

Machine learning and data science

Research Interests

Development of theory and applications in machine learning, big data, information theory, deep learning, manifold learning, statistical learning theory, estimation, graphical models, and random matrix theory. Applications of interest include biology (including medical), finance, ecology, engineering, and navigation.

Awards

Faculty Researcher of the Year, 2023

Department of Mathematics and Statistics

Faculty Graduate Mentor of the Year, 2022

College of Science

Faculty Graduate Mentor of the Year, 2022

Department of Mathematics & Statistics


Publications | Journal Articles

Academic Journal

An asterisk (*) at the end of a publication indicates that it has not been peer-reviewed.

Publications | Other

An asterisk (*) at the end of a publication indicates that it has not been peer-reviewed.

Teaching

STAT 6655 - Machine Learning, Spring 2023
MATH, STAT 6645, 5645 - Mathematical Methods for Data Science, Fall 2022
CS, STAT 6685, 5810, 5890 - Topics in Computer Science (Topic), Fall 2022
STAT 6810 - Machine Learning, Spring 2022
CS, STAT 6685, 5810 - Deep Learning Theory and Applications, Fall 2021
STAT 6810, 5810 - Mathematical Methods for Data Science, Fall 2021
CS, STAT 6685 - Deep Learning Theory and Applications, Spring 2021
STAT 6820 - Principles of Machine Learning, Spring 2021
STAT 5810, 6810 - Mathematical Methods for Data Science, Fall 2020
CS, STAT 6685, 7810 - Deep Learning Theory and Applications, Spring 2020
STAT 6950 - DR: Statistical Learning Theory, Fall 2019
MATH, STAT 6910 - Principles of Machine Learning, Fall 2019
STAT 6910, 7810 - Deep Learning Theory and Applications, Spring 2019
STAT 6910 - Statistical Learning and Data Mining 2, Fall 2018

Graduate Students Mentored

Ben Shaw, Mathematics & Statistics
Haozhe Chen, Mathematics & Statistics
Kelvyn Bladen, Mathematics & Statistics
Scout Jarman, Mathematics & Statistics
Mina Hossain, Mathematics & Statistics, August 2020
Thomas Kerby, Mathematics & Statistics, August 2020
Devin Eddington, Mathematics & Statistics
Jake Rhodes, Mathematics & Statistics, December 2018 - July 2022
Andres Duque, Mathematics & Statistics, November 2018 - July 2022
Teresa White, Mathematics & Statistics, September 2019 - July 2021
Thomas Brower, Mathematics & Statistics, October 2018 - May 2020
Ronak Tali, Mathematics & Statistics, September 2018 - May 2020
Jared Hansen, Mathematics & Statistics, September 2018 - April 2020