Yang Chen

Yang Chen is an Assistant Professor of Statistics and Research Assistant Professor at the Michigan Institute for Data Science (MIDAS), University of Michigan. Her research focuses on statistical methodology and computational algorithms for scientific applications, including Bayesian modeling, hidden Markov models, and applications in astronomy, space science, and epidemiology. She holds a Ph.D. in Statistics from Harvard University and a B.Sc. in Mathematics from the University of Science and Technology of China.

Education:

• Ph.D. in Statistics, Harvard University, 2017
• B.Sc. in Mathematics, University of Science and Technology of China, 2011

Research Interests:

Her work emphasizes computational algorithms for statistical inference, with applications in astronomy (e.g., solar flare prediction, instrument calibration) and epidemiology. Key areas include spatial-temporal data analysis, uncertainty quantification, and machine learning for large-scale imaging data.

Grants & Funding:

• Principal Investigator/Co-Investigator on multiple NSF, NASA, and industry grants totaling over $13M, including space weather modeling, solar physics, and data science initiatives.

Teaching:

Teaches advanced courses in Bayesian data analysis, statistical modeling, and computational methods at the University of Michigan.

Professional Activities:

• Associate Editor for The American Statistician, Statistical Science, and Journal of the American Statistical Association.
• Active in organizing conferences and seminars on astrostatistics, machine learning, and space weather.