Zhanxing Zhu (朱占星)

@ Peking University (北京大学)

Welcome to my homepage!

I am currently an Assistant Professor at School of Mathematical Sciences, Peking University (北京大学) and Beijing Institute of Big Data Research (北京大数据研究院). I am closely affiliated with Deep Learning Lab of Peking University (北京大学深度学习实验室). Previously I obtained my PhD in machine learning from School of Informatics of University of Edinburgh, UK.

My research interests cover methodology/theory of machine learning and artificial intelligence and their applications in various areas.

  1. Methodology/theory: deep learning, reinforcement learning, scalable optimization and Bayesian inference methods
  2. Applications: prediction problems in traffic, data-driven medical imaging, generative models and reinforcement learning for computer graphics and network security

Contact: Room 219, Jingyuan 6th Courtyard, Peking University, Beijing, China (北京大学静园6号院219)

Email: zhanxing.zhu AT pku.edu.cn



Group Members

  • Ph.D students: Bing Yu ( co-supervised with Prof. Weinan E)
  • MPhil students: Ju Xu, Ke Sun (co-supervised with Prof. Zhouchen Lin), Yuanjin Zhu, Junzhao Zhang
  • Undergraduate: Tianyuan Zhang, Jin Ma, Dinghuai Zhang

Academic Roles

  • Area Chair/Senior PC for AISTATS 2017, AAAI 2019

Publications/Preprints (Check our Github page for reproducibility.)

* indicates equal contribution. 

Learning dynamics in deep learning and optimization

Robustness and adversarial learning

MCMC methodology

  • [ECML/PKDD 2019] Ruosi Wan, Mingjun Zhong, Haoyi Xiong and Zhanxing Zhu. Neural Control Variates for Monte Carlo Variance Reduction. The European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases. (To Appear).
  • [AAAI 2019] Kafeng Wang, Haoyi Xiong, Jiang Bian, Zhanxing Zhu, Chengzhong Xu, Zhishan Guo, Jun Huan. SpHMC: Spectral Hamiltonian Monte Carlo. 33rd AAAI Conference on Artificial Intelligence.
  • [ECML/PKDD 2015] Amos Storkey, Zhanxing Zhu and Jinli Hu. Aggregation Under Bias: Renyi Divergence Aggregation and its Implementation via Machine Learning Markets. European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases.
  • Amos Storkey, Zhanxing Zhu, Jinli Hu. A Continuum from Mixtures to Products: Aggregation under Bias. 31st International Conference on Machine Learning (ICML 2014 Workshop on Divergence Methods for Probabilistic Inference).

ML/DL models and applications

" Only in silence the word, only in dark the light, only in dying life: bright the hawk's flight on the empty sky. "

— Ursula K. Le Guin (A Wizard of Earthsea)


Recently, I wrote a Chinese book with several colleagues on the introduction to data science, which is now available for online shopping. "数据科学导引". Wellcome for all kinds of feedback!


  • Ruosi Wan (now research scientist @ Face++)
  • Haoteng Yin (now Ph.D student @ Purdue University)
  • Jingfeng Wu (now Ph.D student @ John Hopkins University)
  • Zizhuo Zhang
  • Mengzhang Li