Yang Chen

Yang Chen

Assistant Professor of Statistics, Research Assistant Professor for MIDAS

About me

“The best thing about being a statistician is that you get to play in everyone’s backyard.” – John Tukey

I am currently an assistant professor at the Department of Statistics at the University of Michigan and a research assistant professor at Michigan Institute for Data Science (MIDAS).

Besides, I hold “two full-time jobs” as a mother of two.

For me, being a mother made me a better professional, because coming home every night to my girls reminded me what I was working for. And being a professional made me a better mother, because by pursuing my dreams, I was modeling for my girls how to pursue their dreams. – Michelle Obama

Education

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

Research Interests

My research interests are statistical methodology and computational algorithms motivated by scientific applications. My past and ongoing projects are focused on the following topics:

  • Bayesian modeling and computation
  • Hidden Markov models and general finite mixture models
  • Applied statistics and machine learning in astronomy and space science
  • Statistical methods for large-scale imaging data
  • Spatial-temporal data analysis
  • Uncertainty quantification for complex models

Selected Recent Publications

Statistical Theory and Methodology

Quantifying Observed Prior Impact in Bayesian Inference

  • David Jones, Robert Trangucci, and Yang Chen. “Quantifying Observed Prior Impact.” Bayesian Analysis, 17 (3) 737 - 764, September 2022. [link]

Video Imputation with Spatial and Temporal Smoothness

  • Hu Sun, Zhijun Hua, Jiaen Ren, Shasha Zou, Yuekai Sun, and Yang Chen. “Matrix Completion Methods for the Total Electron Content Video Reconstruction.” The Annals of Applied Statistics 16, no. 3 (2022): 1333-1358. [link]

  • Hu Sun, Yang Chen, Shasha Zou, Jiaen Ren, Yurui Chang, Zihan Wang, and Anthea Coster. Complete Global Total Electron Content Map Dataset based on a Video Imputation Algorithm VISTA. Nature - Scientific Data 10, 236 (2023). [link]

Matrix Autoregressive Models with Exogeneous Vector Time Series Predictors

  • Hu Sun, Zuofeng Shang, and Yang Chen. “Matrix Autoregressive Model with Vector Time Series Covariates for Spatio-Temporal Data.” (2024). [arXiv preprint]

Applied Statistical Methods in Physical Sciences

Calibration Concordance for Astronomical Instruments via Multiplicative Shrinkage

  • Yang Chen, Xiao-Li Meng, Xufei Wang, David A. van Dyk, Herman L. Marshall, and Vinay L. Kashyap. “Calibration Concordance for Astronomical Instruments via Multiplicative Shrinkage.” Journal of the American Statistical Association 114, no. 527 (2019): 1018-1037. [link]

  • Marshall, Herman L., Yang Chen, Jeremy J. Drake, Matteo Guainazzi, Vinay L. Kashyap, Xiao-Li Meng, Paul P. Plucinsky, Peter Ratzlaff, David A. van Dyk, and Xufei Wang. “Concordance: In-flight Calibration of X-Ray Telescopes without Absolute References.” The Astronomical Journal 162, no. 6 (2021): 254. [link]

Solar Flare Forecasting

  • Yang Chen, Ward B. Manchester, Alfred O. Hero, Gabor Toth, Benoit DuFumier, Tian Zhou, Xiantong Wang, Haonan Zhu, Zeyu Sun, and Tamas I. Gombosi. “Identifying Solar Flare Precursors Using Time Series of SDO/HMI Images and SHARP Parameters.” Space Weather 17, no. 10 (2019): 1404-1426. [link]

  • Hu Sun, Ward Manchester, Meng Jin, Yang Liu, Yang Chen. “Tensor Gaussian Process with Contraction for Multi-Channel Imaging Analysis.” Proceedings of the 40th International Conference on Machine Learning, PMLR 202:32913-32935 (2023). [link]

Applied Statistical Theory and Methods in Epidemiology

Robert Trangucci, Yang Chen, and Jon Zelner. “Modeling Rates of Disease with Missing Categorical Data.”, Annals of Applied Statistics (2023). [link]

Robert Trangucci, Yang Chen, and Jon Zelner. “Identified Vaccine Efficacy for Binary Post-infection Outcomes under Misclassification without Monotonicity.” (2023). [arXiv preprint]

Opportunities

I am recruiting postdocs, Ph.D., master’s, and undergraduate students to join my research group. If you are interested, please send your CV and transcript to my email.

Contact

Address: 445E West Hall 1085 S. Univ. Ave. Ann Arbor, MI 48109, USA

Email: ychenang at umich.edu

Current students

If you want to schedule a meeting with me, the best way is to go to Google Calendar and send a calendar invite to me at one of my available slots.

Past students

Please email me and share your updates on work and life. This is an exciting part of my job!

This webpage is updated every two weeks.