About

I am Jian Xu. I received my Ph.D. in Computational Mathematics and Electronic Information from South China University of Technology (SCUT) in December 2025, under the supervision of Professor Delu Zeng. I am currently a research intern at the RIKEN Center for Advanced Intelligence Project (AIP) in Japan, supervised by Professor Qibin Zhao.

My research lies at the intersection of probabilistic machine learning, stochastic processes, generative modeling, differential equation-based methods, and large language models. I aim to integrate advanced mathematical tools with modern machine learning, with a focus on Bayesian generative models and principled inference, including Gaussian processes and variational inference.

My first-author work has appeared in ICML (Oral, Top 1%), AAAI, AISTATS, TNNLS, and KBS. Several manuscripts are currently under review. I also collaborate closely with Professor John Paisley (Columbia University) on Bayesian machine learning and variational inference.

🎓 Education

• Ph.D. in Computational Mathematics & Electronic Information
  South China University of Technology, 2020 – 2025
  • First-author papers accepted at top-tier conferences, including ICML Oral (Top 1%)
  • Advisor: Prof. Delu Zeng
  • Mentor/host: Prof.Qibin Zhao & Prof. John Paisley
• M.Sc. in Basic Mathematics
  South China University of Technology, 2018 – 2020
  • First-class academic scholarship
  • Advisor: Assoc. Prof. Bingsheng Lin
• B.A. in Business Administration
  Communication University of China, 2013 – 2017
  • Second Prize, National College Student Mathematics Competition

🔬 Research Focus

• Probabilistic Machine Learning
• Deep Gaussian Processes
• Stochastic Differential Equations
• Generative Models & Diffusion Inference
• Variation Inference & Stochastic Processes Models

📝 Selected Publications

• Sparse Inducing Points in Deep Gaussian Processes – ICML 2024 (Oral, Top 1%) https://arxiv.org/pdf/2407.17033
• Sparse Variational Student-t Processes – AAAI 2024 https://arxiv.org/abs/2312.05568
• Neural Operator Variational Inference – IEEE TNNLS https://ieeexplore.ieee.org/abstract/document/10637293
• Fully Bayesian Differential Gaussian Processes – KBS https://www.sciencedirect.com/science/article/abs/pii/S0950705125002345
• Double Normalizing Flows for Bayesian ODEs – AISTATS 2025 https://proceedings.mlr.press/v258/xu25b.html
• Variational Learning of Gaussian Process Latent Variable Models through Stochastic Gradient Annealed Importance Sampling – UAI 2025 https://www.arxiv.org/abs/2408.06710

📬 Contact

• Email: 2713091379@qq.com or jian.xu@a.riken.jp
• Location: Wushan Campus, SCUT, Guangzhou, China

Thanks for visiting! Feel free to contact me or check out my research projects.