Xiang Ye

I am a PhD candidate in the Bayesian Computational Statistics and Modeling Research Group at King Abdullah University of Science and Technology (KAUST), under the supervision of Professor Håvard Rue.我目前在阿卜杜拉国王科技大学（KAUST）攻读统计学博士学位，师从 Håvard Rue 教授，并在贝叶斯计算统计与建模研究组开展研究。

My PhD research focuses on Bayesian latent variable models and joint modelling, from prior specification and model construction to computation and applications. I develop these ideas for directional and circular statistics and implement the resulting methodology for Integrated Nested Laplace Approximation (INLA).我的博士研究围绕贝叶斯潜变量模型与联合建模展开，涵盖先验设定、模型构建、计算方法与实际应用。我将这些思想应用于方向统计与圆周统计，并在集成嵌套拉普拉斯近似（INLA）框架下实现相应方法。

Looking ahead, I am interested in the theory, methodology, and applications of fast Bayesian inference, particularly for increasingly complex and high-dimensional models. I am also interested in bringing Bayesian ideas into modern deep learning, especially generative models, to improve uncertainty quantification and computational efficiency, while encouraging more structured, transparent, and reliable reasoning.未来，我希望继续探索快速贝叶斯推断的理论、方法与应用，尤其关注日益复杂的高维模型。我也期待将贝叶斯思想融入现代深度学习，特别是生成模型，在提升计算效率的同时，更好地量化不确定性，让推理过程更有条理、更透明、更可靠。

I am always happy to discuss new ideas and potential collaborations, especially around statistical methodology, Bayesian computation, and related interdisciplinary problems.我一直乐于交流新想法、探索合作机会，尤其关注统计方法、贝叶斯计算及相关跨学科问题。