معرفی
Haotian Xu is a Harrison Early Career Assistant Professor in the Department of Statistics at the University of Warwick. His research focuses on nonparametric estimation in high-dimensional settings, change point detection, and inference under temporal dependence and contamination. He holds a Ph.D. from the University of Geneva (2021) and an MSc from the University of Illinois at Urbana-Champaign (2015). His postdoctoral work involved collaborations at institutions like Pennsylvania State University and Université Catholique de Louvain.
Key research areas include robust statistical methods, wavelet-based inference, and applications in sensor calibration and functional data analysis. He has developed R packages such as 'changepoints' and 'FragmentCP' for change point detection. Teaching responsibilities include Bayesian Forecasting and Intervention at Warwick and courses in statistical modeling at Penn State and the University of Geneva.
His publications span high-impact journals like the Annals of Statistics and IEEE Transactions, addressing challenges in time series analysis, multivariate modeling, and computational statistics. Current projects emphasize scalable inference for large datasets and fragmented functional data analysis.
