Statistics PhD students at UW–Madison: If you are interested in my research, please do not hesitate to contact me.
Postdocs:
Hyunseok Seung (with Sündüz Keleş)
Wentao Zhan (with Daniel Wright)
PhD students:
Jacob Johnson
Alejandro Calle-Saldarriaga
Felix Jimenez
Dan Drennan
Jiayi (Carrie) Lei
Paul Wiemann (2022-2024)
Jian Cao (2021-2023)
Anirban Chakraborty (2024): Scalable Statistical Methods for Large Spatial and Spatio-Temporal Data
Myeongjong (MJ) Kang (2023): Sparse inverse Cholesky factorization for scalable Gaussian-process inference
Brian Kidd (2022, with Yang Ni): Directed Graphs and Applications
Daniel Zilber (2021, with Debdeep Pati): Application, Methodology, and Theory for Gaussian Processes
Jingjie Zhang (2020): Fast Inference for Multi-Scale and Global Spatial Processes
Marcin Jurek (2020): Scalable Filtering Methods for High-Dimensional Spatio-Temporal Data
Wenlong Gong (2018): Multi-resolution approximations of Gaussian processes for large spatial datasets
Patrick Schmidt (2013, with Tilmann Gneiting): Parametric estimation of loss functions
Maximilian Ruhland (2014, with Tilmann Gneiting): Similarity-based probabilistic forecasting of wind speed
Andreas Knapp (2012): Global Bayesian nonstationary spatial modeling for very large datasets
Andreas Neudecker (2012, in cooperation with Julien Gagneur at Gene Center Munich and Simon Anders at EMBL Heidelberg): A Bayesian hierarchical model for the analysis of RNA sequencing data