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Xiaotian Zheng

I am a Postdoctoral Research Fellow at the Centre for Environmental Informatics in the National Institute for Applied Statistics Research Australia at the University of Wollongong. I work with Andrew Zammit Mangion and Noel Cressie to develop statistical methods for better understanding of the Antarctic environment. The research is part of Securing Antarctica’s Environmental Future (SAEF), an Australian Research Council (ARC) Special Research Initiative that aims to understand, manage, and forecast the environmental changes taking place across the Antarctic region.

My research interests broadly lie in parametric and nonparameteric methods for complex and dependent data, from a Bayesian perspective. I draw motivation from applications in biology, environmental science, epidemiology, and economics. I am also interested in methods for high-dimensional data and scalable algorithms for large data sets. I received my Ph.D. in Statistical Science from the Department of Statistics at the University of California, Santa Cruz, where I worked on mixture modeling for non-Gaussian spatial and temporal processes, advised by Athanasios Kottas and Bruno Sansó.

Recent News

Dec 2022: Talk at Time Series and Forecasting Symposium (The University of Sydney Business School)
(A Mixture Modeling Framework for Temporal Point Processes with Memory)

Oct 2022: Official launch of the ARC initiative SAEF (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)

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)

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.
      (2022 ISBA Section on Environmental Sciences Student Paper Award)

  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]
      (2021 ASA Section on Bayesian Statistical Science Student Paper Award)

Software

  1.   R package and example code for “On Construction and Estimation of Stationary Mixture Transition Distribution Models.” [package] [example]

Teaching

University of California Santa Cruz

  • Graduate Student Instructor: Statistics Laboratory (STAT 7L; 3 quarters)
  • Teaching Assistant: Bayesian Modeling (STAT 207; Graduate; 1 quarter); Classical and Bayesian Inference (STAT 132; Upper-Division; 1 quarter);
    Introduction to Probability Theory (STAT 131; Upper-Division; 3 quarters); Statistics (STAT 5 & STAT 7; Lower-Division; 8 quarters)