I am a postdoctoral researcher in the Department of Statistics and the Institute of Data Science at Texas A&M University, supervised by Dr. Matthias Katzfuss. I obtained my Ph.D. degree in Statistics at King Abdullah University of Science and Technology (KAUST), advised by Dr. Marc Genton. Prior to that, I obtained a B.S. in Mathematics from University of Science and Technology of China.
I have broad research interests in scalable computational methods and theories behind those. Currently in my postdoc, I am working on scalable Gaussian process regression and variable selection, transport maps, and variational Bayes, most of which are based on the Vecchia approximation of Gaussian processes. During my PhD, I studied scalable evaluations of multivariate normal probabilities, mainly exploiting low-rank matrices and efficient quasi-Monte Carlo sampling rules. My research is mostly related to applications in spatial statistics, climate science, and argricultural science. My goal is to make scalable Gaussian-based methods a ready-to-use tool for various machine-learning tasks.
PhD in Statistics, 2020
King Abdullah University of Science and Technology
B.S. in Mathematics, 2014
University of Science and Technology of China
Cao, J., Guinness, J., Genton, M. G., & Katzfuss, M. (2022) Scalable Gaussian-process Regression and Variable Selection using Vecchia Approximations. Journal of Machine Learning Research 23(348), pp.1-30
Cao, J., Durante, D., & Genton, M. G. (2022). Scalable Computation of Predictive Probabilities in Probit Models with Gaussian Process Priors. Journal of Computational and Graphical Statistics 31(3), pp.709-720
Cao, J., Genton, M. G., Keyes, D. E., & Turkiyyah, G. M. (2022). tlrmvnmvt: Computing High-Dimensional Multivariate Normal and Student-t Probabilities with Low-rank Methods in R. Journal of Statistical Software 101, pp.1-25
Cao, J., Genton, M. G., Keyes, D. E., & Turkiyyah, G. M. (2021). Exploiting Low Rank Covariance Structures for Computing High-Dimensional Normal and Student-t Probabilities. Statistics and Computing, 31(1), pp.1-16
Cao, J., Genton, M. G., Keyes, D. E., & Turkiyyah, G. M. (2021). Sum of Kronecker Products Representation and Its Cholesky Factorization for Spatial Covariance Matrices from Large Grids. Computational Statistics & Data Analysis, 157, pp.107165
Cao, J., Genton, M. G., Keyes, D. E., & Turkiyyah, G. M. (2019). Hierarchical-block Conditioning Approximations for High-dimensional Multivariate Normal Probabilities. Statistics and Computing 29, pp.585-598
Huang, J., Fang, F., Turkiyyah, G., Cao, J., Genton, M. G., & Keyes, D. E. (2021). An O(N) Algorithm for Computing Expectation of N-dimensional Truncated Multivariate Normal Distribution I: Fundamentals. Advances in Computational Mathematics 47(5), pp. 1-34
Abdulah, S., Li, Y., Cao, J., Ltaief, H., Keyes, D. E., Genton, M. G., & Sun, Y. (2022). Large-scale Environmental Data Science with ExaGeoStatR. accepted by Environmetrics
Cao, J., Zhang, J., Sun, Z., & Katzfuss, M. (2022) Locally Anisotropic Covariance Functions on the Sphere. submitted