Department of Statistics and Applied Probability
University of California, Santa Barbara
Santa Barbara, CA
Email: mengyang at pstat.ucsb.edu
I am an assistant professor in the Department of Statistics and Applied Probability at UC Santa Barbara. Previously I was an assistant research professor in the Department of Applied Mathematics and Statistics at Johns Hopkins University. Feel free to contact me to work on some interesting research projects together.
- Uncertainty quantification
- Bayesian analysis
- Computer model emulation (numerical methods of partial differential equations)
- Inverse problem/model calibration
- Spatio-temporal models
- functional data analysis
- Tensor methods
- Dimension reduction
2016 Ph.D., Statistics, Duke University
2012 B.Sc., Statistics, Zhejiang University; Honor Degree in Chu Kochen Honors College
Current (Fall 2019) course:
PSTAT 120C: Probability and Statistics (in GauchoSpace)
Please find a complete list of publications and preprints in my google scholar profile.
Selected publications & preprints
- Anderson, K., Johanson, I., Patrick, M., Gu, M., Segall, P., Poland, M., Montgomery-Brown, E. and Miklius, A. (2019). Magma reservoir failure and the onset of caldera collapse at Kilauea Volcano in 2018. (Accepted in Science).
- Gu, M. and Shen, W. (2019). Generalized probabilistic principal component analysis of correlated data. (Accepted in the Journal of Machine Learning Research). (arXiv:1808.10868).
- Gu, M., and Xu, Y. (2019). Fast Nonseparable Gaussian Stochastic Process With Application to Methylation Level Interpolation. (Accepted in the Journal of Computational and Graphical Statistics). (arXiv:1711.11501). ("FastGaSP" R package on CRAN).
- Gu, M. Jointly robust prior for Gaussian stochastic process in emulation. (2019). calibration and variable selection. Bayesian Analysis, 14(3): 857--885. ("RobustGaSP" R package on CRAN).
- Gu, M., Bhattcharjya, D. and Subramanian, D. (2019). Nonparametric estimation of utility functions. (Accepted in AAAI 2020). arXiv:1807.10840.
- Gu, M., Wang, X. and Berger, J. (2018). Robust Gaussian stochastic process emulation. Annals of Statistics. 46(6A): 3038--3066. ("RobustGaSP" R package on CRAN).
- Gu, M., and Wang, L. (2018) Scaled Gaussian stochastic process for computer model calibration and Prediction. SIAM/ASA Journal on Uncertainty Quantification, 6(4): 1555--1583.
- Gu, M., Xie, F. and Wang, L. (2018). A theoretical framework of the scaled Gaussian stochastic process in prediction and calibration. (arXiv:1807.03829). ("RobustCalibration" R package on CRAN).
- Gu, M. and Anderson, K. (2018). Calibration of imperfect mathematical models by multiple sources of data with measurement bias. (arXiv:1810.11664).
- Gu, M. and Berger, J. (2016). Parallel partial Gaussian process emulation for computer models with massive output. Annals of Applied Statistics, 10(3): 1317--1347. ("RobustGaSP" R package on CRAN, "RobustGaSP in MATLAB" package in Github).
- Gu, M., Palomo J. and Berger J. “RobustGaSP” available on CRAN, an R Package for Robust Gaussian Stochastic Process Emulation of complex computer models. arXiv:1801.01874.
- Gu, M. “RobustCalibration” available on CRAN, an R package for robust calibration for imperfect mathematical models.
- Gu, M. "FastGaSP" available on CRAN, an R package for fast and exact computation of Gaussian stochastic process.
- Gu, M. "RobustGaSP in MATLAB" package in Github, a MATLAB package for emulating complex computer model.
Gu, M. (2016). Robust uncertainty quantification and computation for computer models with massive output. PhD Thesis. Duke University.