Dr. Xin Tong

Associate Professor

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Biography

Xin Tong is an Associate Professor of Data Sciences and Operations at the University of Southern California. His current research interests focus on asymmetric statistical learning, addressing challenges in the Neyman-Pearson classification paradigm, data distortion, sampling bias, asymmetric group classification, clustering, partial knowledge clustering, and community detection. His research has been published in distinguished journals, including Science Advances, the Journal of the American Statistical Association, the Journal of the Royal Statistical Society: Series B, and the Journal of Machine Learning Research. Professor Tong's research has received support from the National Science Foundation and the National Institutes of Health.

Research Interests

Asymmetric Statistical Learning Neyman-Pearson Classification Data Distortion Sampling Bias Asymmetric Groups Classification Clustering Partial Knowledge Clustering Community Detection

Courses

DSO-575 Driving Business Transformation DSO-530 Applied Modern Statistical Learning Methods

Requirements for University of Southern California

Master Program
Requirements
GPA Requirement
Required:3
TOEFL
Listening
Required:20
Reading
Required:20
Writing
Required:20
Speaking
Required:20
Total
Required:90
IELTS
Listening
Required:6
Reading
Required:6
Writing
Required:6
Speaking
Required:6
Overall
Required:6.5
GRE General
Prerequisites
Bachelor's degree in Engineering, Math, or Hard Science
Application Checklist
  • Online application
  • Official transcripts
  • Personal Statement
  • Resume/CV
  • Letters of Recommendation (not required for MS CS, but allowed)
Specialization Notes

GRE is NOT required for Master's applicants for 2025-2026.