I am a fifth year PhD candidate in the Department of Statistics at University of California Santa Cruz, where I work on modeling for non-Gaussian processes in time and space. I am advised by Athanasios Kottas and Bruno Sansó. My research interests broadly lie in methods for complex and dependent data. I draw motivations from applications in biological and environmental sciences, social science, and neuroscience. I am also interested in methods for high-dimensional data and scalable algorithms for large data sets.
Recent News
June 2022: Talk at WNAR Annual Meeting (online)
(Nearest-Neighbor Geostatistical Models for Non-Gaussian Data)
Mar 2022: Talk at ISBA EnviBayes Online Seminar
(Nearest-Neighbor Geostatistical Models for Non-Gaussian Data)
Jan 2022: Student Paper Award of the ISBA Section on Environmental Sciences
Sep 2021: Poster at
ICSA Applied Statistics Symposium (online)
(On Construction and Estimation of Stationary Mixture Transition Distribution Models)
Aug 2021: Talk at Joint Statistical Meeting (online)
(On Construction and Estimation of Stationary Mixture Transition Distribution Models)
July 2021: Talk & Poster at
ISBA World Meeting (online)
(Nearest-Neighbor Geostatistical Models for Non-Gaussian Data)
June 2021: Scholarship for UW Biostatistics Summer Institute in Statistics and Modeling in Infectious Diseases
Jan 2021: Student Paper Award of the ASA Section on Bayesian Statistical Science
Preprints and Journal Papers
3. Xiaotian Zheng, Athanasios Kottas, and Bruno Sansó (2021+). Bayesian Geostatistical Modeling for Discrete-Valued Processes.
2. Xiaotian Zheng, Athanasios Kottas, and Bruno Sansó (2021+). Nearest-Neighbor Mixture Models for Non-Gaussian Spatial Processes.
1. Xiaotian Zheng, Athanasios Kottas, and Bruno Sansó (2022). On Construction and Estimation of Stationary Mixture Transition Distribution Models.
Journal of Computational and Graphical Statistics, 31, 283-293.
[arXiv]
[code]
Software
1. R package and example code for “On Construction and Estimation of Stationary Mixture Transition Distribution Models.” [package] [example]
Teaching
Graduate Student Instructor
STAT 7L Statistical Methods for the Biological, Environmental, and Health Sciences Laboratory Fall 2021, Winter 2022, Spring 2022
Teaching Assistant
STAT 207 Intermediate Bayesian Statistical Modeling Spring 2021
STAT 132 Classical and Bayesian Inference Winter 2021
STAT 131 Introduction to Probability Theory Fall 2020, Winter 2020, Fall 2019
STAT 7 Statistical Methods for the Biological, Environmental, and Health Sciences Summer 2021, Summer 2020
STAT 5 Statistics Spring 2020, Summer 2019, Spring 2019, Winter 2019, Fall 2018, Summer 2018