Minh Tang

Minh Tang is an Associate Professor in the Department of Statistics at North Carolina State University (NC State). His research focuses on statistical inference on graphs, dimensionality reduction, and pattern recognition. He holds a Ph.D. in Computer Science from Indiana University (2010), an M.S. from the University of Wisconsin-Milwaukee (2004), and a B.Sc. from Assumption University, Thailand (2001).

Dr. Tang’s work bridges theoretical statistics and applied network science, emphasizing spectral methods for graph analysis. Key contributions include advancements in stochastic blockmodels, random dot product graphs, and latent space models. He has collaborated extensively on topics such as community detection, vertex nomination, and hypothesis testing for network data. His methods have applications in neuroscience, social networks, and machine learning.

Publications span journals like the Annals of Statistics, Journal of Machine Learning Research, and IEEE Transactions on Pattern Analysis and Machine Intelligence. Teaching includes advanced courses on statistical inference in graphs, emphasizing spectral techniques and modern graph theory applications.

• Education:
• Ph.D. in Computer Science, Indiana University, Bloomington, 2010
• M.S. in Computer Science, University of Wisconsin-Milwaukee, 2004
• B.Sc. in Computer Science, Assumption University, Thailand, 2001

Research Themes: Spectral graph theory, network anomaly detection, latent position estimation, and scalable statistical algorithms for large networks.