Shandian Zhe

Abount Me

I will obtain the Ph.D. degree in this December from Computer Science Department of Purdue University. My advisor is Prof. Jennifer Neville. My former advisor is Prof. Alan Qi, who has moved to Ant Financial Service Group, Alibaba.

My research interests mainly lie in probabilistic machine learning (and its various applications). That is, using probabilistic frameworks to formulate learning problems and to infer/estimate model parameters. My research include but are not limited to probabilistic graphical models, Bayesian nonparametric, approximate inference, sparse learning, large-scale machine learning, kernel methods and deep learning. From application side, I have developed probabilistic methods for microarray data analysis, association study for Alzheimer's disease, functional magnetic resonance imaging (fMRI) data analysis, and click-through-rate prediction for online advertising.

Email: szhe at
Office: Computer Science Department, Lawson 2149-21
Address: Lawson 2149-22, 305 N. University Street, West Lafayette, IN 47907-2107

Curriculum Vitae

I will join School of Computing, University of Utah as an assistant professor in Spring 2018.
I am looking for highly motivated students with solid background in probability, linear algebra and/or optimization, and good programming skills. If you are interested in joining my group, welcome to contact me via zhe AT . Please attach your CV in the email.


  • AAAI/SIGAI 2017 Doctoral Consortium Scholarship
  • Google PhD Fellowship for Machine Learning 2016
  • AAAI 2015 Outstanding Student Paper Honorable Mention
  • Pacific Symposium on Biocomputing 2014 travel award
  • Publications

    Source Code

    Working Experience

  • Yahoo! Ad Science and Data team, 05/2016-08/2016
  • Yahoo! Labs, 05/2015-08/2015
  • NEC Laboratories America, INC. 05/2014-08/2014
  • Professional Serverices

  • Reviewer for International Conference for Machine Learning (ICML) 2014, 2015
  • Reviewer for Neural Information Processing Systems (NIPS) 2015, 2016, 2017
  • Reviewer for Journal of Machine Learning Research (JMLR)
  • Reviewer for IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI)
  • Reviewer for IEEE Transactions on Knowledge and Data Engineering (TKDE)
  • Program Committee member for The 2nd International Conference on Data Analytics, 2013
  • Program Committee member for The 2nd Workshop on Scalable Machine Learning: Theory and Applications, IEEE International Conference on Big Data, 2014
  • Program Committee member for The Third IEEE International Conference on Multimedia Big Data, 2017
  • Program Committee member for KDD 2017 workshop on AdKDD and TargetAD
  • Program Committee member for NIPS 2017 workshop on Advances in Approximate Bayesian Inference